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diff --git a/_site/assets/js/search-data.json b/_site/assets/js/search-data.json
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@@ -2,1300 +2,1405 @@
"doc": "(10/08/24) Discrod AMA 2024",
"title": "Discord AMA Session Summary - LAI & DAO Labs",
"content": "Speakers: . | Aaditya, Founder of LAI | Harsh Joshi, Founder of DAO Labs | . Audience: . | Students and working professionals | . ",
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"doc": "(10/08/24) Discrod AMA 2024",
"title": "Key Discussion Points",
"content": "How Students Can Grab Internship Opportunities . Aaditya and Harsh shared insights into finding and securing internships in today’s competitive landscape. They emphasized the importance of networking, leveraging platforms like LinkedIn, attending industry meetups, and participating in relevant online communities. They advised students to tailor their resumes to highlight skills and projects that align with potential internship roles, and to proactively reach out to companies or professionals in their field of interest. How to Make a Good GitHub Repo . The speakers discussed best practices for creating a compelling GitHub repository. Key points included: . | Organized Structure: Use clear directories and maintain a clean project structure. | Descriptive README: Include a comprehensive README file with project overview, setup instructions, usage examples, and contribution guidelines. | Documentation: Regularly update documentation and ensure code is well-commented. | Version Control: Utilize branches effectively and maintain a consistent commit history. | Company Evaluation: Companies often evaluate candidates by reviewing their GitHub profiles. Therefore, good documentation is crucial as it showcases your skills, project quality, and attention to detail. | . Essentials of Proper Documentation and README Files . Effective documentation is crucial for the usability and maintainability of a project. Aaditya and Harsh outlined essential elements of documentation: . | README Files: Should provide a summary of the project, installation steps, usage instructions, and contact information. | Code Comments: Write clear comments to explain complex logic or code sections. | Contributing Guidelines: Provide instructions for contributors on how to report issues, submit changes, and follow coding standards. | . Ideas for Final Year Projects . The session included brainstorming for innovative final year project ideas. Some suggestions were: . | AI-Powered Chatbots: Develop chatbots with advanced conversational abilities for specific domains. | Blockchain-Based Applications: Explore blockchain for secure transactions or decentralized apps. | IoT Solutions: Create IoT-based systems for smart home or environmental monitoring. | Augmented Reality: Build AR applications for educational or entertainment purposes. | . Doubt Solving . The AMA also featured a Q&A segment where students and professionals posed their queries. The speakers addressed questions on various topics such as career advice, project development challenges, and industry trends. This interactive segment provided personalized guidance and solutions to specific issues faced by the attendees. ",
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"doc": "(10/08/24) Discrod AMA 2024",
"title": "Conclusion",
"content": "The AMA session with Aaditya and Harsh provided valuable insights into career development, project management, and technical documentation. Attendees gained practical advice on securing internships, creating effective GitHub repositories, and enhancing project documentation, along with exploring innovative ideas for their final year projects. The event was a great opportunity for the community to engage directly with industry leaders and address their career and technical queries. ",
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"doc": "(10/08/24) Discrod AMA 2024",
"title": "(10/08/24) Discrod AMA 2024",
"content": " ",
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"doc": "(13/01/24) Jamie AI Voice Assistant Online Meetup",
"title": "The Jamie AI Voice Assistant Online Meetup",
"content": "Summary: . The Jamie AI Voice Assistant Online Meetup, a collaborative effort between Lucknow AI lab and TFUG Lucknow, highlighted an innovative venture to enhance digital accessibility through AI. This online event, held on January 13, 2024, via Google Meet, assembled a diverse group of technology aficionados, developers, and AI enthusiasts to discuss and explore the potential of voice-assisted technology in making digital interfaces more user-friendly. Date: January 13, 2024 Time: 2:30 PM Platform: Google Meet . Organizers: Lucknow AI lab and TFUG Lucknow. Key Contributors: Neel, Surabh, Manso (JavaScript Expert), Mukesh (Streamlit Guru), Jaswir (CEO & AI Developer) . View Recording . ",
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"doc": "(13/01/24) Jamie AI Voice Assistant Online Meetup",
"title": "Event Highlights",
"content": "Introduction and Overview . | The meetup provided an insightful overview of the Jamie AI Voice Assistant project, emphasizing its mission to simplify the digital experience for users. This initiative represents a significant step towards bridging the gap between complex digital technologies and the everyday user. | Spearheaded by a dynamic team comprising Manso, Mukesh, and Jaswir, the project leverages their collective expertise in JavaScript, Streamlit, and AI development to create a versatile and intuitive voice assistant. | Collaboration between Lucknow AI lab and TFUG Lucknow played a pivotal role in organizing and managing this enriching event, which saw significant participation from individuals across various sectors. | . Technical Exploration and Demonstrations . Project Insight . | Attendees were introduced to the foundational goals of Jamie AI, designed to act as a tech-savvy companion that offers assistance with a broad spectrum of digital tasks, from mundane to complex. | . Technical Infrastructure . | A deep dive into the technical underpinnings of Jamie AI, showcasing how Manso’s JavaScript prowess and Mukesh’s Streamlit expertise have contributed to an engaging user interface and responsive front-end experience. | The session highlighted the advanced algorithms employed for image analysis and natural language processing, enabling Jamie AI to understand and execute a wide range of voice commands effectively. | . Demonstrations and Applications . | Real-time demonstrations of Jamie AI in action provided tangible examples of its potential, illustrating how it can assist users in managing smart home devices and navigating digital platforms, thereby reducing the technological barriers for the less digitally savvy. | . Community Engagement and Visionary Future . Engaging the Community . | A significant emphasis was placed on community engagement, with participants invited to contribute ideas for improvements, new features, and potential use cases, fostering a collaborative development environment. | . Vision for the Future . | The Jamie AI team shared their ambitious vision for the voice assistant, discussing plans to expand its functionalities to include navigation assistance, healthcare management, and educational support, among other applications. | . Conclusion and Acknowledgements . The Jamie AI Voice Assistant Online Meetup concluded on a high note, with participants and organizers alike excited about the future directions of the project. The event underscored the transformative potential of Jamie AI in making technology accessible to a broader audience and highlighted the critical role of community involvement in driving technological innovation. Special thanks were extended to Manso, Mukesh, and Jaswir for their dedication and contributions, as well as to all participants for their engagement and enthusiasm. This event report captures the spirit and objectives of the Jamie AI Voice Assistant meetup, reflecting on the collaborative effort to democratize access to technology through AI-driven solutions. ",
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"title": "(13/01/24) Jamie AI Voice Assistant Online Meetup",
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"doc": "(21/01/24) Startup Success Days India 2023",
"title": "Startup Success Days India 2023",
"content": "Summary: . Startup Success Days India 2023, organized by GDG Lucknow in partnership with TFUG Lucknow, was a pivotal event held at Club Orchid, Lucknow. This event series was crafted to unite Founders, Developers, Mentors, VCs, Industry leaders, Googlers, and enthusiasts to discuss and share insights on the forefront of technological innovation, with a special focus on Generative AI, Google Cloud, Google Maps, Android, Web3, and Language Solutions. Date and Time: January 21, 10:00 AM – 4:00 PM . Location: Club Orchid, H-306 Faizabad Road, Lucknow, 226028 . Key Contributors: GDG Lucknow Team & TFUG Lucknow Team . * . *Visit Page ** . ",
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"doc": "(21/01/24) Startup Success Days India 2023",
"title": "Event Highlights",
"content": "Introduction and Overview . | Inaugural Address: Vasundhara, the GDG Lucknow Organizer, kicked off the event, setting the tone for a day filled with insightful discussions and presentations. | Key Themes: The event revolved around crucial tech and development themes including AI, Career Development, Cloud Computing, Community Building, Enterprise/Business Solutions, Networking, and Women Techmakers. | Objective: The essence of Startup Success Days was to empower startups to leverage Google’s tools and platforms for product development and business growth, while nurturing local ecosystem collaborations. | . Session Summaries . Morning Sessions . | Discussions began with a deep dive into State Management, exploring its essentials, applications, and best practices. | A Practical Guide to GraphQL provided attendees with actionable insights into implementing GraphQL in their projects. | Thriving on Thin Air session offered strategies for launching businesses with minimal resources, emphasizing efficiency and innovation. | The focus then shifted to the World of IoT using a hybrid cloud approach, highlighting the integration of IoT technologies with cloud computing. | AI/ML in Education sector discussion underscored the transformative potential of artificial intelligence and machine learning in enhancing educational experiences and outcomes. | . Afternoon Sessions . | A detailed exploration of Pattern Matching in programming languages, discussing its significance and applications. | Panel Discussion: Fostering a New Generation of Developers, facilitated a dialogue among experts on nurturing tech talent and innovation in the developer community. | The discussion on Decentralization of Web Architecture examined the shift towards a more distributed and user-empowered internet structure. | A Session on Adapting Large Language Models (LLMs) to Low Resource Languages: This session, led by Ankit, delved into the challenges and solutions associated with customizing LLMs for languages with limited digital resources. Ankit provided insights into techniques for training models efficiently, ensuring linguistic diversity and accessibility in AI-driven applications. Ankit also participated in the panel discussion, contributing his expertise to broader conversations about developer support and community growth. | A session on Kubernetes covered the essentials of using Kubernetes for managing containerized applications, focusing on its importance in modern software development. | . Conclusion . The event concluded with closing remarks, reflected on the day’s learnings and encouraged participants to continue exploring and innovating with the tools and knowledge shared. Startup Success Days India 2023 was not just a conference; it was a beacon for startups and technologists, highlighting the importance of collaboration, continuous learning, and technological advancement. Special thanks were extended to all speakers, for invaluable contributions, and to the organizing teams of GDG and TFUG Lucknow for making this event a resounding success. This daylong journey through various facets of technology and business underscored the vibrant potential of the Lucknow tech community and its role in shaping the future of innovation. ",
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"doc": "(21/01/24) Startup Success Days India 2023",
"title": "(21/01/24) Startup Success Days India 2023",
"content": " ",
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"doc": "23-24-May-2024-Hack-To-Crack-1.0",
"title": "Event Highlights",
"content": "Introduction and Overview . | Hack To Crack 1.0 was an exhilarating 24 hours AI/ML hackathon focused on tackling real-world challenges. | This event has been Orgnised by TFUG Lucknow in collabration with GDG lucknow and Lucknow AI labs. | The event was open to all skill levels, from seasoned data scientists to beginners in AI/ML. | Participants had the opportunity to work in teams, exploring various fields such as computer vision, natural language processing, and reinforcement learning. | . Participation and Engagement . | 33 participants joined the event, forming 9 teams. | The hackathon encouraged collaboration, innovation, and showcasing of talent in AI/ML technologies. | Participants worked on developing intelligent algorithms and implementing predictive models. | . Projects and Domains . | Automated AI/ML System for Detecting and Mitigating Online Fraud (Online Fraud Detection) | AI-Multilingual-Chatbot (Natural Language Processing) | Batch Audio Transcription Tool (Speech Recognition and Translation) | Bridging the Language Gap: AI-Powered Local Language Transcription and Translation (Natural Language Processing) | Spotify clone (Music Streaming) | Whisper: AI-Powered Local Exploration with RAG-Gemini WhatsApp Bot (Conversational AI) | ChatWithYourPDF (Document Analysis and Conversational AI) | DocGPT (Document Processing and AI) | . Winners . | First Place: Automated AI/ML System for Detecting and Mitigating Online Fraud Team Name: Veg Kabab, Team: Utkarsh Tiwari | Second Place: Bridging the Language Gap: AI-Powered Local Language Transcription and Translation Team Name: Quaraforce. Team: Aditya Singh, Gaurangi Prakash, Vishal Sarup mathur, Suyash pandey | Third Place: Batch Audio Transcription Tool (Speech Recognition and Translation) Team Name: Pheonix, Team: Anshika Shahi, Divyansh Singh | . Impact and Innovation . | The event provided a platform for pushing the boundaries of AI innovation. | Participants worked on solutions to empower and assist underserved communities. | The hackathon fostered the development of AI technologies for social good, addressing challenges faced by individuals with disabilities and underserved populations. | . Conclusion . Hack To Crack 1.0 successfully brought together AI/ML enthusiasts to collaborate, innovate, and create impactful solutions. The diverse range of projects demonstrated the potential of AI/ML technologies in solving real-world problems and contributing to a more inclusive and equitable society. ",
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"doc": "23-24-May-2024-Hack-To-Crack-1.0",
"title": "23-24-May-2024-Hack-To-Crack-1.0",
"content": "AI/ML Community Event - Summary : . 23-24 May 2024 (24 hour Hackathon) . Hack To Crack 1.0: An AI/ML Hackathon . View Event Details . ",
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"doc": "(25/05/24) Gen AI Awadh Summit",
"title": "Gen AI Awadh Summit 2024",
"content": "Summary: . The Gen AI Awadh Summit, held on May 25, 2024, brought together tech enthusiasts, industry experts, and innovators at the Centre for Advanced Studies, Dr. APJ Abdul Kalam Technical University in Lucknow, India. Organized by TFUG Lucknow and supported by Hunto AI, the summit delved into the latest advancements in artificial intelligence with a special focus on generative AI. The event featured a series of keynotes, workshops, and a hackathon, showcasing AI’s transformative impact across industries. Date: May 25, 2024 Time: 10:00 AM Venue: 1st Floor, SSB Hall, Dr. APJ Abdul Kalam Technical University, Lucknow, India-226031 . Organizers: TFUG Lucknow Sponsors: Hunto AI Collaborations: Google Developer Groups Lucknow . View Location on Map . ",
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"doc": "(25/05/24) Gen AI Awadh Summit",
"title": "Event Highlights",
"content": "Registration and Welcome . | Attendees gathered at 10:00 AM for registration, followed by a welcome address and introduction by the organizers. | . Keynote Sessions and Technical Talks . Generative AI Fundamentals . | Speaker: Aaditya (Senior Research Engineer, Organizer TFUG Lucknow) | Aaditya provided a comprehensive introduction to generative AI, highlighting its applications and potential to revolutionize industries. | . Large Language Models in Cybersecurity: Google’s Sec-PaLM and Cloud Security AI Workbench . | Speaker: Madhurendra Sachan | Madhurendra explored the integration of large language models like Sec-PaLM in enhancing cybersecurity, with a focus on Google’s AI security tools. | . Crafting Visions with Gemini: How Text Becomes Visual Masterpieces . | Speaker: Prashant Shukla (Research Associate at IIT Delhi, Co-organizer TFUG Lucknow) | Prashant demonstrated how Gemini AI transforms text into visual creations, highlighting the power of generative models in visual design. | . Afternoon Workshops and Panel Discussions . Fine-Tuning Google’s Large Language Model Gemma with Keras NLP . | Speaker: Abhishek Sahu (Organizer GDG Lucknow, Co-organizer TFUG Lucknow) | Abhishek discussed fine-tuning Google’s language model Gemma, showcasing practical applications in natural language processing. | . Panel Discussion: The Evolution of AI: Past, Present, and Future . | A panel of experts engaged in a lively discussion on AI’s growth and future possibilities, with emphasis on its societal and ethical implications. | . Hackathon and Community Showcase . | The event concluded with a hackathon winner’s felicitation and community project showcase, celebrating innovative AI-driven solutions developed during the summit. | . Conclusion . The Gen AI Awadh Summit left attendees inspired and eager to further explore the potential of AI. The event was a testament to the collaborative spirit of the AI community in Lucknow and the broader impact AI can have on society. ",
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"title": "(25/05/24) Gen AI Awadh Summit",
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"doc": "(26/11/23) Meetup",
"title": "AI/ML Community Meetup Event",
"content": "Summary : . All notable discussions and insights from the AI/ML community event are documented in this file. Sunday, 26 November 2023 . The event featured experienced speakers Ankit, Abhishek, and Neil, who shared their insights on various aspects of AI/ML. 🎤 . View Slides . ",
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"doc": "(26/11/23) Meetup",
"title": "Event Highlights",
"content": "Introduction and Overview . | Introduction of speakers Ankit, Abhishek, and Neil, bringing many years of experience in data science and AI/ML. | . AI/ML Domain Focus . | Discussion on Neil’s work in the AI/ML domain, emphasizing the expertise brought to the event. | . Lucknow AI Initiative . | Insight into the Lucknow AI initiative aimed at fostering an AI-focused community. | . ChatGPT and AI Development . | Exploration of technologies like ChatGPT and the need for understanding AI development processes. | . Plan . | Formation of Two Groups: In the following months, we will form two distinct groups - a basic group for beginners and an intermediate group. | Course Selection: The basic group will commence their journey with a Python course, while the intermediate group will dive into a machine learning course. | Weekly Meetups: Post-completion of each course module, we’ll organize weekly meetups. These sessions are designed for doubt clarification and brainstorming, ensuring a thorough understanding of the material. | Educational Video Series: We plan to produce concise, informative videos summarizing each module. These videos will be uploaded to the Lucknow AI YouTube channel. | Benefits of Video Posting: . | Enhanced Visibility: Students’ contributions will be showcased, amplifying their learning achievements. | Website Feature: Contributions will be featured on the Lucknow AI website, providing a platform for wider recognition. | Resume Enhancement: Students can include these accomplishments in their resumes, adding significant value. | Social Sharing: Encouraging students to share their learning journey on LinkedIn and other social platforms for broader professional networking. | . | GitHub Profile Development: Participants are encouraged to create a GitHub profile and consistently upload their module code. - This practice aims to develop a professional and impactful GitHub presence. | Through these initiatives, we aim to foster a robust learning environment, encouraging both skill development and professional growth within the AI community. | . AI as a Continuous Journey . | Emphasis on AI as a journey of continuous learning and exploration, with a series of milestones. | . Community Building and Learning Path . | Plans for activities to support beginners in AI, including mentorship and industry interactions. | . Addressing the ‘Why AI?’ Question . | Discussion on the significance of AI, highlighting recent advancements and impacts of technologies like GPT models. | . Practical Application and Internships . | The importance of practical experience and internships in AI for societal and national impact. | . Networking and Community Support . | Stress on networking within the AI community and supporting each other in learning and career development. | . Future Engagement Strategies . | Plans for future sessions, learning paths, and strategies to maintain active participation. | . Participant Interaction . | Participants engaged in discussions, sharing their interests and backgrounds. | . Concluding Remarks . | Encouragement for ongoing learning in AI/ML, stressing its continuous nature. | . ",
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"doc": "(27/04/24) GDSC WOW Lucknow 2024",
"title": "GDSC WOW Lucknow 2024",
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"title": "(27/04/24) GDSC WOW Lucknow 2024",
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"doc": "(27/02/24) Build, Train & Deploy Workshop",
"title": "Build, Train & Deploy Workshop",
"content": "Summary: . The “Build, Train & Deploy” workshop, hosted by TFUG Lucknow and collaborated by LUCKNOW AI LABS, provided a deep dive into the world of AI and ML, ranging from basic neural networks to advanced generative AI models. This event offered a comprehensive educational experience, combining theoretical knowledge with practical coding exercises. Date: February 27, 2024 . The workshop has been featured by the Experience Speakers: Ankit, a Senior AI Research Engineer at Saama and an expert in NLP and AI/ML. and Abhishek Sahu, Senior Software Engineer at BFC Capital P. Ltd, having expertise in the Retrieval-Augmented Generation (RAG), and Flutter. View Slides . ",
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"doc": "(27/02/24) Build, Train & Deploy Workshop",
"title": "Event Highlights",
"content": "Introduction and Overview . | Held at Shri Ramswaroop College Of Engineering and Management, Lucknow, this workshop attracted over 200 participants, including AI and ML enthusiasts, students, and professionals eager to enhance their understanding and skills in AI technologies. | The workshop featured an in-depth exploration at every stage of learning in AI/ML concepts, facilitated by hands-on sessions with Google Colab, and provided insights into effective project management using GitHub. | Sessions covered ranged from the foundational principles of neural networks to practical implementations of advanced models like BERT and GPT, emphasizing the application of AI in solving real-world problems. | . Detailed Sessions Breakdown . Ankit’s Comprehensive AI/ML Overview . | Foundational AI Concepts: Ankit began with a strong foundation in neural networks, detailing their design and functionality. This set the stage for understanding more complex AI models. | Advanced AI Models and Techniques: The presentation covered embeddings, attention mechanisms, transformers, and the intricacies of models such as BERT and GPT. Ankit provided practical coding examples, illustrating these concepts’ applications in natural language processing and beyond. | Project Management with GitHub: An essential part of modern AI project development involves using tools like GitHub for collaboration and version control. Ankit’s session offered valuable insights into leveraging GitHub for managing complex AI projects. | . Abhishek Sahu’s RAG Model Workshop . | Tackling Large Language Models Challenges: Abhishek addressed specific issues inherent in LLMs, such as data hallucination and the need for up-to-date information. Through the lens of the RAG model, he presented solutions that enhance model accuracy and reliability. | Practical Demonstrations: Participants were treated to hands-on demonstrations of RAG implementations, highlighting the model’s ability to improve upon traditional LLMs by incorporating additional data sources for more accurate output. | . Audience Engagement and Learning Outcomes . | Diverse Participant Group: The workshop was designed to cater to a wide range of participants, from beginners to seasoned professionals. The diverse audience contributed to rich discussions and a dynamic learning environment. | Skill Enhancement and Knowledge Acquisition: Attendees gained valuable skills in AI model development, from basic neural networks to advanced techniques in generative AI, coupled with practical experience in project management using GitHub. | Community Building and Collaboration: The event fostered a sense of community among AI enthusiasts, encouraging ongoing collaboration, exploration, and innovation in the field of AI. | . Conclusion . The “Build, Train & Deploy” workshop by LUCKNOW AI LABS and TFUG Lucknow was a transformative event in AI and ML education. It not only provided participants with a thorough understanding of AI technologies but also equipped them with the practical skills necessary for their application in real-world scenarios. The workshop underscored the importance of continuous learning, collaboration, and innovation in the ever-evolving AI landscape, setting a precedent for future educational initiatives in the AI community. ",
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"doc": "(27/02/24) Build, Train & Deploy Workshop",
"title": "(27/02/24) Build, Train & Deploy Workshop",
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"doc": "(27/01/24) Meetup",
"title": "AI/ML Community Meetup Event",
"content": "Summary : . All notable discussions and insights from the AI/ML community event are documented here. Saturday, 27 January 2024 . The event featured an experienced speaker Prashant Shukla who shared his insights on various aspects of AI/ML. 🎤 . View Slides . ",
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"doc": "(27/01/24) Meetup",
"title": "Event Highlights",
"content": "Introduction and Overview . | The TensorFlow User Group (TFUG) Lucknow, in collaboration with Lucknow AI Labs, hosted an informative webinar on advanced computer vision techniques, focusing on image processing and the OpenCV library. The event brought together a diverse group of computer vision professionals, researchers, and community groups to foster knowledge sharing and collaboration. AI/ML Domain Focus | The session delved into the intricacies of computer vision, with a specific emphasis on state-of-the-art image processing techniques and the powerful OpenCV library. speaker highlighted the real-world applications of these technologies across various industries, showcasing their potential to revolutionize domains such as autonomous vehicles, medical imaging, and visual analytics. Lucknow AI Initiative | The webinar was part of a larger collaborative effort between TFUG Lucknow and Lucknow AI Labs to promote technology education and drive innovation in the field of artificial intelligence. This initiative aims to empower the local community with cutting-edge knowledge and skills, fostering a thriving ecosystem of AI enthusiasts and professionals. | . ChatGPT and AI Development . | Discussions also touched upon the advancements in AI-generated visual content, with a focus on the capabilities of models like ChatGPT in generating and processing images. speaker explored the implications of these developments for the field of computer vision and the potential for AI to transform the way we interact with and analyze visual data. | . Plan . | To support ongoing learning and skill development, the organizers shared plans to provide participants with access to comprehensive learning resources post-event. These resources, including tutorials, documentation, and code samples, will enable attendees to continue advancing their knowledge and expertise in computer vision and OpenCV. | Furthermore, the organizers expressed their intention to explore additional collaborative events focused on specific AI subdomain areas. These targeted sessions will provide deeper insights into niche topics and foster specialized skill development within the community. | . AI as a Continuous Journey . | The speaker emphasized that image processing and computer vision are rapidly evolving fields, necessitating a continuous learning approach. They stressed the importance of staying updated with the latest advancements, techniques, and tools to remain at the forefront of this dynamic domain. | . Community Building and Learning Path . | The webinar served as a platform for networking and knowledge exchange among peers and related communities. Attendees had the opportunity to connect with like-minded individuals, share experiences, and explore potential collaborations. | The event provided a solid foundation for members to further their skills in computer vision and OpenCV. The organizers outlined a learning path that included hands-on workshops, project-based learning, and mentorship opportunities to support participants in their journey towards mastery. | . Addressing the ‘Why AI?’ Question . | The speaker addressed the fundamental question of why AI and computer vision matter in today’s world. They highlighted the diverse real-world applications of image processing and computer vision, ranging from autonomous vehicles and robotics to medical diagnostics and surveillance systems. — By showcasing the tangible impact of these technologies, the event emphasized the significance of investing time and effort in learning and advancing in this field. | . Practical Application and Internships . | To bridge the gap between theory and practice, the webinar demonstrated applied uses of OpenCV across various industries. speaker shared real-world case studies and examples, illustrating how computer vision techniques are being leveraged to solve complex problems and drive innovation. | The organizers also discussed the importance of internships and practical experience in the field of AI and computer vision. They encouraged participants to seek out opportunities to work on real-world projects and gain hands-on experience, enhancing their employability and industry readiness. | . Networking and Community Support . | The event facilitated meaningful interactions and networking opportunities among members of TFUG, Lucknow AI Labs, and other related groups. Attendees had the chance to connect with industry experts, researchers, and fellow enthusiasts, fostering a supportive community that encourages knowledge sharing and collaboration. | . Future Engagement Strategies . | To sustain the momentum and support ongoing learning, the organizers shared plans to provide additional learning resources post-webinar. These resources, including tutorials, documentation, and curated content, will enable participants to deepen their understanding of computer vision and OpenCV. | The organizers also expressed interest in hosting recurring computer vision-focused gatherings, such as workshops, hackathons, and expert talks. These events will provide a platform for continuous skill development, networking, and exposure to the latest trends and technologies in the field. | . Participant Interaction . | The webinar incorporated an interactive Q&A session, allowing participants to engage with the speaker and seek clarification on various aspects of computer vision and OpenCV. The discussions were lively and insightful, reflecting the enthusiasm and curiosity of the attendees. | . Concluding Remarks . | The event concluded on a high note, with the speaker emphasizing the immense potential and vibrant future of the Lucknow AI community. They encouraged participants to continue their learning journey, embrace the challenges and opportunities in the field of computer vision, and contribute to the growth of the AI ecosystem in the region. | The organizers expressed their gratitude to the speaker, participants, and collaborators for their support and engagement, reaffirming their commitment to fostering a thriving AI community in Lucknow. | . ",
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"doc": "(29/06/24) Build with AI 2024",
"title": "Build with AI",
"content": "Summary: . The “Build with AI” event series, hosted by Google Developer Groups, was an immersive two-day experience designed to equip developers with the latest AI tools and integration techniques. Held on June 29 and 30, 2024, the event featured a range of sessions from industry experts, hands-on workshops, and interactive discussions. Here’s a detailed overview of the event highlights and key takeaways. Date: June 29-30, 2024 Venue: Online Event . Organizers: Google Developer Groups Collaborations: Various AI and ML Experts . ",
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"doc": "(29/06/24) Build with AI 2024",
"title": "Event Highlights",
"content": "Day 1 - June 29 . LLM INFERENCE using Mediapipe with Gemma . | Speaker: Kartikey Rawat (Open Source Manager at CodeLabs | Google Developer Expert in ML) Kartikey delved into using Mediapipe for LLM inference, showcasing its capabilities and applications in AI projects. His session provided insights into leveraging Mediapipe for real-time AI solutions. | . AI-Powered Malware: The Evolving Threat Landscape . | Speaker: Shrutirupa Banerjee (Senior Security Researcher at Quick Heal Technologies) Shrutirupa discussed the rise of AI-powered malware and the associated security challenges. Her talk highlighted strategies for mitigating threats and enhancing security measures against evolving AI-driven cyber risks. | . Localised Intelligence in AI for a Richer AI-UX . | Speaker: Harsh Joshi (Founder, DAO Studio) Harsh explored how localized intelligence can improve AI user experiences. He emphasized the importance of tailoring AI solutions to specific regional and cultural contexts to enhance user engagement. | . Day 2 - June 30 . LLM Powered Application using Advanced RAG Methodology SELF-RAG . | Speaker: Jyotishko Biswas (Head of AI for HP Global Treasury) Jyotishko presented on automating contract compliance in Fortune 500 firms using SELF-RAG methodology. His session provided practical insights into applying advanced RAG techniques for efficient document management. | . Generative AI Fundamentals . | Speaker: Ankit Pal (Senior Research Engineer at Saama | Organizer TFUG Lucknow) Ankit covered the fundamentals of Generative AI, including its principles and applications. His talk was designed to provide a solid foundation for understanding and implementing Generative AI technologies. | . Workshop: Intro to RAG with Gemini and Custom Data . | Speaker: Abhishek Sahu (Senior Software Engineer at BFC | Co-Organizer GDG, TFUG Lucknow) Abhishek conducted a hands-on workshop on RAG with Gemini, guiding attendees through integrating custom data into RAG workflows. The session was interactive and aimed at practical implementation. | . Networking & Swag Distribution . The event featured a networking session, allowing participants to connect with speakers and peers. Google swag was distributed, adding a fun conclusion to the event. Conclusion . The “Build with AI” series successfully provided valuable knowledge and skills on various aspects of AI. Attendees gained practical experience with AI tools, learned from industry experts, and connected with the developer community, making the event a significant step in advancing their AI journey. ",
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"doc": "(29/06/24) Build with AI 2024",
"title": "(29/06/24) Build with AI 2024",
"content": " ",
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"doc": "(31/08/24) Google I/O Extended Lucknow",
"title": "Google I/O Extended Lucknow 2023",
"content": "Summary: . The Google I/O Extended event in Lucknow took place at Integral University on Kursi Road, offering a platform for developers, designers, and tech enthusiasts to gather, learn, and exchange insights on the latest trends in technology. The event was packed with engaging sessions from expert speakers, interactive activities, and plenty of networking opportunities. Here’s a comprehensive overview of the event highlights and key takeaways. Date: September 10, 2023 Time: 10:00 AM Venue: Integral University, Kursi Road, Dashauli, Uttar Pradesh 226026 . Organizers: GDG Lucknow Collaborations: Google Developer Groups India . View Location on Map . ",
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"doc": "(31/08/24) Google I/O Extended Lucknow",
"title": "Event Highlights",
"content": "Registration and Welcome . | The event kicked off at 10:00 AM with registration, where attendees were required to present their Entry Pass and a valid photo ID for verification. No on-site registration was available, and participants were reminded to bring their passes in advance. | . Key Sessions and Insights . Learning Containers Before You Jump on the Clouds . | Speaker: Mritunjay Sharma (Software Engineer at Chainguard) Mritunjay provided a deep dive into the role of containers in modern cloud-native applications. He shared best practices for deploying containers efficiently, emphasizing their benefits for scalability and security. | . Beyond the Pixel: The Human Side of Design . | Speaker: Vanshita Singh (Co-Organizer at GDG Noida, WTM Ambassador, UI/UX Designer) Vanshita explored the emotional and psychological elements of design, emphasizing the importance of user-centered design principles that go beyond aesthetics. Her talk highlighted how understanding user behavior can lead to more effective design solutions. | . Quiz Session . A fun and interactive quiz session was conducted to test participants’ knowledge on tech topics covered during the event. This engaging activity offered a lively break for all attendees. Integrating Gemini AI with Jetpack Compose . | Speaker: Akash Verma Akash introduced the audience to Gemini AI and demonstrated how to integrate it with Jetpack Compose, Google’s modern UI toolkit for Android. He showed how developers can leverage AI to create more responsive and intelligent Android apps. | . Build a Seamless and Intuitive Product with Jakob Nielsen’s Heuristic Principles . | Speaker: Aryendra Prakash Singh (Co-Organizer at GDG Noida, Design Lead at Publicis Sapient) Aryendra presented Jakob Nielsen’s 10 Usability Heuristics, providing practical advice on applying these principles to create intuitive and user-friendly products. | . Introduction to Project IDX and Firebase Genkit | Build an Agent-Powered App with Generative AI . Attendees were introduced to Google’s latest tools, Project IDX and Firebase Genkit, which facilitate the development of AI-powered applications. This session showcased how to build apps that integrate Generative AI, offering new ways to enhance app functionality. Networking & Swag Distribution . The event concluded with a networking session, where participants had the opportunity to engage with speakers and fellow developers. Google swag was distributed, adding a fun and memorable touch to the end of the day. Conclusion . Google I/O Extended Lucknow 2023 was a highly informative and engaging event. Attendees gained valuable insights into containers, AI integration, product design, and usability, all while building stronger connections within the local developer community. ",
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"title": "(31/08/24) Google I/O Extended Lucknow",
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"doc": "AI Baithak",
"title": "🎉 AI Baithak ke Sadasya 🎉",
"content": "Meet the tech-savvy members of our community! 🚀 These are the masterminds driving innovation with AI, machine learning, and blockchain. ",
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"doc": "AI Baithak",
"title": "🎯 Rag Rishi",
"content": "Name: Abhishek Sahu Description: Abhishek is a flutter developer by profession, but his heart truly beats for RAG (Retrieval-Augmented Generation). Wherever he sees documents, the first words out of his mouth are, “Arey, ispe RAG kyun nahi laga rahe ho?” His passion for optimizing retrieval systems and vector databases makes him a true RAG devotee 📚. But wait, there’s more—Abhishek is also into actual Raag! 🎶 When he’s not diving into neural networks, he’s probably singing classical Indian ragas, proving that his skills extend beyond just tech. Whether it’s a complex query or a classical tune, Rag Rishi will always find the right note! 🎼 More about Rag Rishi . ",
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"doc": "AI Baithak",
"title": "🛠️ Machine Mantri",
"content": "Name: Prashant Description: Prashant, aka Machine Mantri, runs his own ministry of robots and AI! From making bots play drums 🥁 to ruling the world of Arduino and edge devices, he’s got it all under control. When he’s not coding a bot’s next move, you’ll find him binge-watching his favorite anime for even more futuristic inspiration 🌟. If there’s a tech problem, Machine Mantri will solve it—probably with a side of robot rock music! 🎸🤖 More about Machine Mantri . ",
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"doc": "AI Baithak",
"title": "🔗 Blockchain Babu",
"content": "Name: Harsh Joshi Description: Harsh’s mantra is simple: “Centralization ko chhodo, sab kuch blockchain pe lao!” Whether it’s AI, chai, or even your friendships, Harsh believes everything should run on a decentralized ledger 🔐. From smart contracts to Web3, Blockchain Babu ke hote hue, even your chai breaks might get decentralized! ☕ More about Blockchain Babu . ",
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"doc": "AI Baithak",
"title": "🎤 Speech Shastri",
"content": "Name: Gauraangi Description: Gauraangi, aka Speech Shastri, doesn’t just hear voices—she makes AI listen to them! A master of turning sound into smarts, she’s the one who cracked the code at Hack2Crack Hackathon, leaving everyone wondering if she secretly trains AI by making it recite Sanskrit shlokas. 📜 . From building speech models to fine-tuning them like a classical Raag 🎶, Speech Shastri’s mantra is simple: “If it talks, I’ll make AI understand it!” When she’s not making machines listen, she’s probably convincing them to sing back! 🎵 More about Speech Shastri . ",
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"doc": "AI Baithak",
"title": "🤖 Diffusion Dada",
"content": "Name: Kaif Description: Kaif is your go-to guy when it comes to anything related to image-based models. You’ve got a blurry image, an artifact problem, or just a random curiosity? Don’t worry, Kaif’s first reaction is always, “Chalo Stable Diffusion lagate hai ispe!” His life revolves around collecting data, fine-tuning models, and optimizing the diffusion process as if it were his morning chai ☕. Whether it’s upscaling, inpainting, or generating new visuals, Kaif can tackle it all—just don’t be surprised if he starts giving life advice based on latent spaces. When in doubt, let Diffusion Dada sort your pixels out! 🎨 More about Diffusion Dada . ",
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"doc": "AI Baithak",
"title": "🎙️ Join Our Discord",
"content": "Got any questions related to images, RAG, blockchain, or AI? Feel free to ask our members on Discord! . Join Lucknow AI Discord . ",
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"title": "AI Baithak",
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+ "doc": "Commonly Asked Questions",
+ "title": "Frequently Asked Questions",
+ "content": "Q: How can I start studying AI? . To start studying AI, begin by learning programming languages like Python, as it’s commonly used in AI development. You can also take online courses in AI, machine learning, and data science from platforms like Coursera, edX, or Udemy. Start with the basics of algorithms, data structures, and AI fundamentals. Q: How can I apply AI to real-world problems? . Once you’ve learned the fundamentals, try applying AI to real-world problems by building projects such as a chatbot, image classifier, or recommendation system. You can also participate in Kaggle competitions or contribute to open-source AI projects to gain experience. Q: What are the career opportunities in AI? . AI offers a wide range of career opportunities, including roles like AI engineer, data scientist, machine learning engineer, NLP specialist, and AI research scientist. Many industries, from healthcare to finance, are actively looking for AI talent to help build intelligent systems. Q: What are the best online courses to learn AI? . Some of the best online courses include: . | Coursera: \"Machine Learning\" by Andrew Ng, \"Deep Learning Specialization\" by DeepLearning.AI | edX: \"Introduction to Artificial Intelligence\" from MIT | Udemy: \"Artificial Intelligence A-Z™: Learn How to Build an AI\" | Fast.ai: Practical deep learning courses designed for beginners. | . Q: How important is math for learning AI? . Mathematics is essential for understanding the algorithms behind AI. Linear algebra, probability, statistics, and calculus are particularly important in areas like machine learning and deep learning. However, many practical AI tools and libraries abstract the math, allowing you to start building without deep mathematical knowledge. ",
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+ "url": "/docs/layout/FAQ/Commonly%20Asked%20Questions/",
+
+ "relUrl": "/docs/layout/FAQ/Commonly%20Asked%20Questions/"
+ },"42": {
"doc": "Contact Us",
"title": "Contact Us",
"content": " ",
"url": "/docs/Contact/",
"relUrl": "/docs/Contact/"
- },"41": {
+ },"43": {
+ "doc": "Contact Us",
+ "title": "Get in Touch",
+ "content": " ",
+ "url": "/docs/Contact/",
+
+ "relUrl": "/docs/Contact/"
+ },"44": {
+ "doc": "FAQs",
+ "title": "FAQs",
+ "content": " ",
+ "url": "/docs/layout/FAQ/FAQs/",
+
+ "relUrl": "/docs/layout/FAQ/FAQs/"
+ },"45": {
+ "doc": "LAI FAQs",
+ "title": "Frequently Asked Questions",
+ "content": "Q: What is Lucknow AI Labs? . Lucknow AI Labs is a nonprofit organization dedicated to growing awareness about artificial intelligence (AI) and its applications. We focus on educating individuals, businesses, and communities on AI technologies while providing hands-on learning opportunities and resources. Q: Who can benefit from Lucknow AI Labs’ programs? . Our programs are open to students, developers, entrepreneurs, and professionals from all industries who are interested in learning more about AI. We welcome anyone who wants to explore how AI can improve their skills or help their organization. Q: How is Lucknow AI Labs funded? . As a nonprofit, we rely on donations, grants, and sponsorships to fund our activities. We also collaborate with educational institutions and other organizations to support our mission of spreading AI knowledge. Q: How does Lucknow AI Labs ensure inclusivity in AI education? . We are committed to making AI education accessible to everyone, regardless of their background. Our workshops and events are designed to be inclusive, with resources for beginners and opportunities for underserved communities to learn about AI. Q: How can I support Lucknow AI Labs? . You can support us by volunteering, donating, or participating in our events and workshops. Additionally, sharing our mission and helping spread AI awareness in your community contributes to our cause. ",
+ "url": "/docs/layout/FAQ/LAI%20FAQs/",
+
+ "relUrl": "/docs/layout/FAQ/LAI%20FAQs/"
+ },"46": {
+ "doc": "LAI FAQs",
+ "title": "LAI FAQs",
+ "content": " ",
+ "url": "/docs/layout/FAQ/LAI%20FAQs/",
+
+ "relUrl": "/docs/layout/FAQ/LAI%20FAQs/"
+ },"47": {
+ "doc": "Volunteer FAQs",
+ "title": "Frequently Asked Questions",
+ "content": "Q: How can I volunteer at Lucknow AI Labs? . You can volunteer by filling out the application form on our website or by contacting us directly via email. We welcome individuals with a passion for AI, education, and community outreach to join our mission of spreading AI awareness. Q: Do I need AI or technical expertise to volunteer? . While having AI or technical expertise is beneficial for certain roles, it is not a requirement for all volunteer positions. We also need volunteers for administrative tasks, event organization, outreach, and content creation. We provide training and guidance to help volunteers succeed in their roles. Q: What is the time commitment for volunteering? . The time commitment varies depending on the role. Some volunteer positions may require a few hours a week, while others may be more involved during specific events or projects. We are flexible and will work with you to find a commitment level that suits your schedule. Q: Can I volunteer remotely? . Yes, many of our volunteer opportunities, such as content creation, social media management, and technical support, can be done remotely. We strive to make volunteering accessible to people from all locations. Q: What are the benefits of volunteering with Lucknow AI Labs? . Volunteering with Lucknow AI Labs gives you the chance to contribute to AI awareness, develop your skills, and gain experience working in a nonprofit focused on cutting-edge technology. You’ll also have the opportunity to network with AI professionals and make a positive impact in your community. Q: Will I receive training or support as a volunteer? . Yes, we provide training and guidance to all volunteers, especially for roles that require specific skills. Our team will support you throughout your volunteering journey, ensuring you feel confident and equipped to contribute effectively. Q: Can I volunteer if I’m a student? . Absolutely! We encourage students to volunteer as it’s a great way to learn more about AI and gain hands-on experience. Whether you're studying AI, computer science, or any other field, we have opportunities that will allow you to contribute meaningfully. ",
+ "url": "/docs/layout/FAQ/Volunteer%20FAQs/",
+
+ "relUrl": "/docs/layout/FAQ/Volunteer%20FAQs/"
+ },"48": {
+ "doc": "Volunteer FAQs",
+ "title": "Volunteer FAQs",
+ "content": " ",
+ "url": "/docs/layout/FAQ/Volunteer%20FAQs/",
+
+ "relUrl": "/docs/layout/FAQ/Volunteer%20FAQs/"
+ },"49": {
"doc": "Volunteer Opportunities",
"title": "Volunteer Opportunities at Lucknow AI",
"content": ". | Content Development and Education | Technical and IT Support | Creative and Multimedia | Community Engagement and Outreach | Research and Development | Organizational and Administrative Support | General Volunteer Application Form | . ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#volunteer-opportunities-at-lucknow-ai",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#volunteer-opportunities-at-lucknow-ai"
- },"42": {
+ },"50": {
"doc": "Volunteer Opportunities",
"title": "Content Development and Education",
"content": ". | Content Creation: Help in articles, blogs, educational content on AI/ML. | Workshops/Webinars: Helping in Conducting and facilitating educational sessions. | Mentoring: Guiding Juniors/students in AI/ML. | . Opportunities in this category are ideal for those with a knack for teaching and content creation. ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#content-development-and-education",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#content-development-and-education"
- },"43": {
+ },"51": {
"doc": "Volunteer Opportunities",
"title": "Technical and IT Support",
"content": ". | IT Management: Support for digital infrastructure and resource management. | GitHub Maintenance: Managing PRs and project upkeep. | Website Management: Updating and ensuring website functionality. | . Technical roles . ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#technical-and-it-support",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#technical-and-it-support"
- },"44": {
+ },"52": {
"doc": "Volunteer Opportunities",
"title": "Creative and Multimedia",
"content": ". | Graphic Design: Creating visual content for digital platforms and events. | Photography/Videography: Documenting events for promotional use. | . These roles are perfect for creatively inclined individuals with skills in design and multimedia. ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#creative-and-multimedia",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#creative-and-multimedia"
- },"45": {
+ },"53": {
"doc": "Volunteer Opportunities",
"title": "Community Engagement and Outreach",
"content": ". | Community Outreach: Engaging and promoting the mission in various communities. | Social Media: Managing online groups and content dissemination. | Group Administration: Overseeing Discord and WhatsApp groups. | . Engagement roles are suited for those with strong communication skills and a passion for community building. ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#community-engagement-and-outreach",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#community-engagement-and-outreach"
- },"46": {
+ },"54": {
"doc": "Volunteer Opportunities",
"title": "Research and Development",
"content": ". | Research Projects: Collaborative innovation and project coordination in AI/ML. | . Ideal for individuals interested in cutting-edge AI/ML research and development. ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#research-and-development",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#research-and-development"
- },"47": {
+ },"55": {
"doc": "Volunteer Opportunities",
"title": "Organizational and Administrative Support",
"content": ". | Fundraising: Assisting in fundraising and sponsor relations. | Legal/Compliance: Ensuring legal adherence and managing intellectual property. | Translation/Localization: Making content accessible in multiple languages. | Event Organization: Planning and executing meetups and events. | . These roles require organizational skills and attention to detail, ideal for those who excel in administrative tasks. ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#organizational-and-administrative-support",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#organizational-and-administrative-support"
- },"48": {
+ },"56": {
"doc": "Volunteer Opportunities",
"title": "General Volunteer Application Form",
"content": ". | Fill the form given below ! | . Join the movement to make a difference in the community by volunteering with us. Whether you’re looking to gain new skills, meet like-minded individuals, we have a variety of opportunities available. By filling out our application form, you’ll be taking the first step towards becoming part of a dynamic team dedicated to Accelearte AI Awareness in Lucknow. Our volunteer program is designed to be flexible and accommodating, so whether you have a few hours a week or a few days a month, we have a role that’s right for you. So why wait? Fill out our application form today and start making a difference in the lives of others!” . Loading… ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#general-volunteer-application-form",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/#general-volunteer-application-form"
- },"49": {
+ },"57": {
"doc": "Volunteer Opportunities",
"title": "Volunteer Opportunities",
"content": " ",
"url": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/",
"relUrl": "/docs/Volunteer%20Opportunities%20at%20Lucknow%20AI/"
- },"50": {
+ },"58": {
"doc": "Buttons",
"title": "Buttons",
"content": " ",
"url": "/docs/ui-components/buttons/",
"relUrl": "/docs/ui-components/buttons/"
- },"51": {
+ },"59": {
"doc": "Buttons",
"title": "Table of contents",
"content": ". | Basic button styles . | Links that look like buttons | Button element | . | Using utilities with buttons . | Button size | Spacing between buttons | . | . ",
"url": "/docs/ui-components/buttons/#table-of-contents",
"relUrl": "/docs/ui-components/buttons/#table-of-contents"
- },"52": {
+ },"60": {
"doc": "Buttons",
"title": "Basic button styles",
"content": "Links that look like buttons . Link button . Link button Link button Link button . Link button . [Link button](https://just-the-docs.com){: .btn } [Link button](https://just-the-docs.com){: .btn .btn-purple } [Link button](https://just-the-docs.com){: .btn .btn-blue } [Link button](https://just-the-docs.com){: .btn .btn-green } [Link button](https://just-the-docs.com){: .btn .btn-outline } . Button element . GitHub Flavored Markdown does not support the button element, so you’ll have to use inline HTML for this: . Button element <button type=\"button\" name=\"button\" class=\"btn\">Button element</button> . ",
"url": "/docs/ui-components/buttons/#basic-button-styles",
"relUrl": "/docs/ui-components/buttons/#basic-button-styles"
- },"53": {
+ },"61": {
"doc": "Buttons",
"title": "Using utilities with buttons",
"content": "Button size . Wrap the button in a container that uses the font-size utility classes to scale buttons: . Big ass button . Tiny ass button . <span class=\"fs-8\"> [Link button](https://just-the-docs.com){: .btn } </span> <span class=\"fs-3\"> [Tiny ass button](https://just-the-docs.com){: .btn } </span> . Spacing between buttons . Use the margin utility classes to add spacing between two buttons in the same block. Button with space Button . Button with more space Button . [Button with space](https://just-the-docs.com){: .btn .btn-purple .mr-2 } [Button](https://just-the-docs.com){: .btn .btn-blue } [Button with more space](https://just-the-docs.com){: .btn .btn-green .mr-4 } [Button](https://just-the-docs.com){: .btn .btn-blue } . ",
"url": "/docs/ui-components/buttons/#using-utilities-with-buttons",
"relUrl": "/docs/ui-components/buttons/#using-utilities-with-buttons"
- },"54": {
+ },"62": {
"doc": "Callouts",
"title": "Callouts",
"content": "New (v0.4.0) . Markdown does not include support for callouts. However, you can style text as a callout using a Markdown extension supported by kramdown: block IALs. Common kinds of callouts include highlight, important, new, note, and warning. These callout names are not pre-defined by the theme: you need to define your own names. When you have configured the color and (optional) title for a callout, you can apply it to a paragraph, or to a block quote with several paragraphs, as illustrated below.1 . An untitled callout . {: .highlight } A paragraph . A paragraph . A single paragraph callout . {: .note } A paragraph . A paragraph . {: .note-title } > My note title > > A paragraph with a custom title callout . My note title . A paragraph with a custom title callout . A multi-paragraph callout . {: .important } > A paragraph > > Another paragraph > > The last paragraph . A paragraph . Another paragraph . The last paragraph . {: .important-title } > My important title > > A paragraph > > Another paragraph > > The last paragraph . My important title . A paragraph . Another paragraph . The last paragraph . An indented callout . > {: .highlight } A paragraph . A paragraph . Indented multi-paragraph callouts . > {: .new } > > A paragraph > > > > Another paragraph > > > > The last paragraph . A paragraph . Another paragraph . The last paragraph . Nested callouts . {: .important } > {: .warning } > A paragraph . A paragraph . Opaque background . {: .important } > {: .opaque } > <div markdown=\"block\"> > {: .warning } > A paragraph > </div> . A paragraph . | You can put the callout markup either before or after its content. ↩ . | . ",
"url": "/docs/ui-components/callouts/",
"relUrl": "/docs/ui-components/callouts/"
- },"55": {
+ },"63": {
"doc": "Code",
"title": "Code",
"content": " ",
"url": "/docs/ui-components/code/",
"relUrl": "/docs/ui-components/code/"
- },"56": {
+ },"64": {
"doc": "Code",
"title": "Table of contents",
"content": ". | Inline code | Syntax highlighted code blocks | Code blocks with rendered examples | Mermaid diagram code blocks . | Using a local mermaid library | Using mermaid with AsciiDoc | . | Copy button | . ",
"url": "/docs/ui-components/code/#table-of-contents",
"relUrl": "/docs/ui-components/code/#table-of-contents"
- },"57": {
+ },"65": {
"doc": "Code",
"title": "Inline code",
"content": "Code can be rendered inline by wrapping it in single back ticks. Lorem ipsum dolor sit amet, <inline code snippet> adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. ",
"url": "/docs/ui-components/code/#inline-code",
"relUrl": "/docs/ui-components/code/#inline-code"
- },"58": {
+ },"66": {
"doc": "Code",
"title": "Heading with <inline code snippet> in it.",
"content": "Lorem ipsum dolor sit amet, `<inline code snippet>` adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. ## Heading with `<inline code snippet>` in it. ",
"url": "/docs/ui-components/code/#heading-with-inline-code-snippet-in-it",
"relUrl": "/docs/ui-components/code/#heading-with-inline-code-snippet-in-it"
- },"59": {
+ },"67": {
"doc": "Code",
"title": "Syntax highlighted code blocks",
"content": "Use Jekyll’s built-in syntax highlighting with Rouge for code blocks by using three backticks, followed by the language name: . // Javascript code with syntax highlighting. var fun = function lang(l) { dateformat.i18n = require('./lang/' + l) return true; } . ```js // Javascript code with syntax highlighting. var fun = function lang(l) { dateformat.i18n = require('./lang/' + l) return true; } ``` . ",
"url": "/docs/ui-components/code/#syntax-highlighted-code-blocks",
"relUrl": "/docs/ui-components/code/#syntax-highlighted-code-blocks"
- },"60": {
+ },"68": {
"doc": "Code",
"title": "Code blocks with rendered examples",
"content": "To demonstrate front end code, sometimes it’s useful to show a rendered example of that code. After including the styles from your project that you’ll need to show the rendering, you can use a <div> with the code-example class, followed by the code block syntax. If you want to render your output with Markdown instead of HTML, use the markdown=\"1\" attribute to tell Jekyll that the code you are rendering will be in Markdown format… This is about to get meta… . Link button . [Link button](https://just-the-docs.com){: .btn } . <div class=\"code-example\" markdown=\"1\"> [Link button](https://just-the-docs.com){: .btn } </div> ```markdown [Link button](https://just-the-docs.com){: .btn } ``` . ",
"url": "/docs/ui-components/code/#code-blocks-with-rendered-examples",
"relUrl": "/docs/ui-components/code/#code-blocks-with-rendered-examples"
- },"61": {
+ },"69": {
"doc": "Code",
"title": "Mermaid diagram code blocks",
"content": "New (v0.4.0) . Mermaid allows you to add diagrams and visualizations using Markdown code blocks. It is disabled by default. However, you can turn on support for mermaid by adding a mermaid key to your _config.yml. The minimum configuration requires a version key (matching a version in jsDelivr): . mermaid: # Version of mermaid library # Pick an available version from https://cdn.jsdelivr.net/npm/mermaid/ version: \"9.1.3\" . Additional configuration options are loaded through _includes/mermaid_config.js. By default, the contents of the file are the empty object: . // _includes/mermaid_config.js {} . This loads the default settings. The contents of this object should follow mermaid’s configuration API. For example, to override the theme, change _includes/mermaid_config.js to: . // _includes/mermaid_config.js { theme: \"forest\" } . Once mermaid is installed, it can be used in markdown files. The markdown for a simple flowchart example might look like the following: . ```mermaid graph TD; A-->B; A-->C; B-->D; C-->D; ``` . which renders: . graph TD; A-->B; A-->C; B-->D; C-->D; . Note: for demonstration purposes, we’ve enabled mermaid on this site. It is still disabled by default, and users need to opt-in to use it. Using a local mermaid library . To load a local version of mermaid, also use the path key to specify the location of the library; e.g. mermaid: version: \"10.1.0\" # for (v10+) path: \"/assets/js/mermaid.esm.min.mjs\" # for (<v10): # path: \"/assets/js/mermaid.min.js\" # Note: copy both `mermaid.esm.min.mjs` (v10+) or `mermaid.min.js` (<v10) and the associated # `.map` file from the specified version of `mermaid/dist` to `/assets/js/`. For mermaid versions >=10, this file is imported directly as an ESM module (rather than as a plain <script> tag); users should use the mermaid.esm.min.mjs file. In contrast, for mermaid versions <10, this file is loaded as a script tag; it should be a standalone CJS file (i.e. mermaid.min.js). Mermaid versions 10.0 - 10.1 (and possibly, future releases) still encode relative imports in mermaid.esm.min.mjs. Local users must copy all of the contents of the dist folder to the specified path (preserving the relative location of the files). Just the Docs is actively monitoring mermaid releases; an upstream fix is planned. Using mermaid with AsciiDoc . Users of AsciiDoc (e.g. via jekyll-asciidoc) may need additional configuration to use mermaid. By default, AsciiDoc generates HTML markup that mermaid cannot properly parse. The simplest way to resolve this is to use a passthrough block: . ++++ <pre class=\"language-mermaid\"> graph TD; A-->B; A-->C; B-->D; C-->D; </pre> ++++ . Alternatively, community member @flyx has contributed a Ruby extension that does not require extra markup. The extension is available as a GitHub Gist. Thank you to @flyx! . The asciidoctor-diagram extension which also supports mermaid is not recommended for use with Just the Docs, since it requires separate configuration e.g. for theming, and is known to not be trivial to set up. ",
"url": "/docs/ui-components/code/#mermaid-diagram-code-blocks",
"relUrl": "/docs/ui-components/code/#mermaid-diagram-code-blocks"
- },"62": {
+ },"70": {
"doc": "Code",
"title": "Copy button",
"content": "New (v0.4.0) . The copy button for code blocks can be enabled or disabled via the enable_copy_code_button key in _config.yml. By default, the value of this key is false; users need to opt-in. # For copy button on code enable_copy_code_button: true . Note that this feature requires JavaScript; if JavaScript is disabled in the browser, this feature will not work. In addition, this feature uses navigator.clipboard, which is only available in secure contexts (such as over HTTPS). If the site is viewed in an insecure context, the copy button will not work (relevant issue: #1202). ",
"url": "/docs/ui-components/code/#copy-button",
"relUrl": "/docs/ui-components/code/#copy-button"
- },"63": {
+ },"71": {
"doc": "Color",
"title": "Color Utilities",
"content": " ",
"url": "/docs/utilities/color/#color-utilities",
"relUrl": "/docs/utilities/color/#color-utilities"
- },"64": {
+ },"72": {
"doc": "Color",
"title": "Table of contents",
"content": ". | Light Greys | Dark Greys | Purples | Blues | Greens | Yellows | Reds | . All the colors used in Just the Docs have been systematized into a series of variables that have been extended to both font color and background color utility classes. ",
"url": "/docs/utilities/color/#table-of-contents",
"relUrl": "/docs/utilities/color/#table-of-contents"
- },"65": {
+ },"73": {
"doc": "Color",
"title": "Light Greys",
"content": "| Color value | Font color utility | Background color utility | . | grey-lt-000 | .text-grey-lt-000 | .bg-grey-lt-000 | . | grey-lt-100 | .text-grey-lt-100 | .bg-grey-lt-100 | . | grey-lt-200 | .text-grey-lt-200 | .bg-grey-lt-200 | . | grey-lt-300 | .text-grey-lt-300 | .bg-grey-lt-300 | . ",
"url": "/docs/utilities/color/#light-greys",
"relUrl": "/docs/utilities/color/#light-greys"
- },"66": {
+ },"74": {
"doc": "Color",
"title": "Dark Greys",
"content": "| Color value | Font color utility | Background color utility | . | grey-dk-000 | .text-grey-dk-000 | .bg-grey-dk-000 | . | grey-dk-100 | .text-grey-dk-100 | .bg-grey-dk-100 | . | grey-dk-200 | .text-grey-dk-200 | .bg-grey-dk-200 | . | grey-dk-250 | .text-grey-dk-250 | .bg-grey-dk-250 | . | grey-dk-300 | .text-grey-dk-300 | .bg-grey-dk-300 | . ",
"url": "/docs/utilities/color/#dark-greys",
"relUrl": "/docs/utilities/color/#dark-greys"
- },"67": {
+ },"75": {
"doc": "Color",
"title": "Purples",
"content": "| Color value | Font color utility | Background color utility | . | purple-000 | .text-purple-000 | .bg-purple-000 | . | purple-100 | .text-purple-100 | .bg-purple-100 | . | purple-200 | .text-purple-200 | .bg-purple-200 | . | purple-300 | .text-purple-300 | .bg-purple-300 | . ",
"url": "/docs/utilities/color/#purples",
"relUrl": "/docs/utilities/color/#purples"
- },"68": {
+ },"76": {
"doc": "Color",
"title": "Blues",
"content": "| Color value | Font color utility | Background color utility | . | blue-000 | .text-blue-000 | .bg-blue-000 | . | blue-100 | .text-blue-100 | .bg-blue-100 | . | blue-200 | .text-blue-200 | .bg-blue-200 | . | blue-300 | .text-blue-300 | .bg-blue-300 | . ",
"url": "/docs/utilities/color/#blues",
"relUrl": "/docs/utilities/color/#blues"
- },"69": {
+ },"77": {
"doc": "Color",
"title": "Greens",
"content": "| Color value | Font color utility | Background color utility | . | green-000 | .text-green-000 | .bg-green-000 | . | green-100 | .text-green-100 | .bg-green-100 | . | green-200 | .text-green-200 | .bg-green-200 | . | green-300 | .text-green-300 | .bg-green-300 | . ",
"url": "/docs/utilities/color/#greens",
"relUrl": "/docs/utilities/color/#greens"
- },"70": {
+ },"78": {
"doc": "Color",
"title": "Yellows",
"content": "| Color value | Font color utility | Background color utility | . | yellow-000 | .text-yellow-000 | .bg-yellow-000 | . | yellow-100 | .text-yellow-100 | .bg-yellow-100 | . | yellow-200 | .text-yellow-200 | .bg-yellow-200 | . | yellow-300 | .text-yellow-300 | .bg-yellow-300 | . ",
"url": "/docs/utilities/color/#yellows",
"relUrl": "/docs/utilities/color/#yellows"
- },"71": {
+ },"79": {
"doc": "Color",
"title": "Reds",
"content": "| Color value | Font color utility | Background color utility | . | red-000 | .text-red-000 | .bg-red-000 | . | red-100 | .text-red-100 | .bg-red-100 | . | red-200 | .text-red-200 | .bg-red-200 | . | red-300 | .text-red-300 | .bg-red-300 | . ",
"url": "/docs/utilities/color/#reds",
"relUrl": "/docs/utilities/color/#reds"
- },"72": {
+ },"80": {
"doc": "Color",
"title": "Color",
"content": " ",
"url": "/docs/utilities/color/",
"relUrl": "/docs/utilities/color/"
- },"73": {
+ },"81": {
"doc": "About Us",
"title": "Welcome To Lucknow AI",
"content": "Scientia potentia est (knowledge is power) . Hi , Thank you all for joining the community! . I wanted to share the story behind why we started this and what drives us. I recently moved to Lucknow and wanted to connect with fellow developers, open-source enthusiasts, and hackers. However, I found that Lucknow lacks such a technology culture and community. I remember wishing as a college student that I had a mentor to guide me and clarify my doubts. I want the next generation to have those opportunities. So I spoke with friends from Lucknow who now work at various companies and agreed to give back by mentoring youth interested in AI & ML. With that goal, We founded Lucknow AI to advance AI literacy and skills through collaborative workshops, meetups, paper discussions, and community growth. I am Aaditya (Ankit), a senior research engineer at Saama AI Research Lab with over 6+ years in core AI research. I love hacking things together, building open-source tools, and publishing state-of-the-art research. You can find more about my background & research at aadityaura.github.io . You might be surprised to know that no one in the Lucknow AI community is paid or sponsored. We are just a group of coding geeks and hackers who are passionate about growing the local AI ecosystem! . We nurture Lucknow AI like our own child, volunteering time outside work or college to support the community. Seniors mentor newcomers not due to any obligation but out of a genuine desire to uplift. We contribute open-source code, curate datasets, brainstorm ideas, analyze research papers and more in the quest to push the boundaries of what AI can achieve. And we do it together as one unstoppable, collaborative force! . This is a safe space where you can learn, teach, create, and grow. Imagine the breakthrough innovations we can create when we come together as a supportive, tight-knit community! Let’s put Lucknow on the map in AI and have fun along the way. If you share this vision, then you have found your tribe. Welcome home! . Excited for the days ahead, ~ Lucknow AI . ",
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"doc": "About Us",
"title": "About Us",
"content": " ",
"url": "/docs/configuration/",
"relUrl": "/docs/configuration/"
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+ },"83": {
"doc": "Resources",
"title": "Table of contents",
"content": ". | Awesome Low Resource Indian Languages Hub | Learning Resources | . ",
"url": "/docs/customization/#table-of-contents",
"relUrl": "/docs/customization/#table-of-contents"
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"doc": "Resources",
"title": "1. AI-Career-Toolkit",
"content": ". ",
"url": "/docs/customization/#1-ai-career-toolkit",
"relUrl": "/docs/customization/#1-ai-career-toolkit"
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"doc": "Resources",
"title": "🚀 AI-Career-Toolkit",
"content": "A comprehensive resource hub for launching and advancing careers in AI, ML, and related fields. ",
"url": "/docs/customization/",
"relUrl": "/docs/customization/"
- },"78": {
+ },"86": {
"doc": "Resources",
"title": "🌟 What’s Inside",
"content": ". | 📝 Resume Templates: Tailored for AI/ML roles | 💼 Portfolio Project Ideas: Inspire your next showcase project | 🎤 Interview Prep: Common questions and best practices | 🔍 Job Search Strategies: Tips for finding and landing AI positions | 🗺️ Learning Roadmaps: Curated paths for different AI specializations | 📊 Industry Insights: Stay updated with the latest AI trends | . ",
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"relUrl": "/docs/customization/#-whats-inside"
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+ },"87": {
"doc": "Resources",
"title": "Resume Templates",
"content": "| Repository | Description | Stars | Last Updated | . | home | A beautiful portfolio template for developers | | | . | Portfolio-Website-Template | A simple and elegant portfolio template | | | . | freemo | A free, modern portfolio template | | | . | portfolio-template-v2 | A sleek, customizable portfolio template | | | . | free-developer-portfolio-template | A modern, responsive portfolio template for developers | | | . | albert-html | A clean and minimalist portfolio template | | | . | portfolio | A versatile portfolio template with various sections | | | . | diy-portfolio | A customizable, DIY portfolio template | | | . ",
"url": "/docs/customization/#resume-templates",
"relUrl": "/docs/customization/#resume-templates"
- },"80": {
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"doc": "Resources",
"title": "🎯 Our Mission",
"content": "To empower the next generation of AI professionals with practical tools, templates, and knowledge to stand out in a competitive job market. ",
"url": "/docs/customization/#-our-mission",
"relUrl": "/docs/customization/#-our-mission"
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"doc": "Resources",
"title": "🤝 Contributing",
"content": "We welcome contributions! Whether you’re sharing your success story, a helpful resource, or improving existing content, your input helps the community grow. ",
"url": "/docs/customization/#-contributing",
"relUrl": "/docs/customization/#-contributing"
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"doc": "Resources",
"title": "📚 Start Your AI Career Journey",
"content": "Explore the toolkit, build your skills, and take the next step in your AI career. Your future in AI starts here! . AI-Career-Toolkit is a community-driven project. Use these resources as inspiration and adapt them to showcase your unique skills and experiences. ",
"url": "/docs/customization/#-start-your-ai-career-journey",
"relUrl": "/docs/customization/#-start-your-ai-career-journey"
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"doc": "Resources",
"title": "2. Learning Resources",
"content": ". ",
"url": "/docs/customization/#2-learning-resources",
"relUrl": "/docs/customization/#2-learning-resources"
- },"84": {
+ },"92": {
"doc": "Resources",
"title": "An Ultimate Compilation of AI Resources for Mathematics, Machine Learning and Deep Learning",
"content": " ",
"url": "/docs/customization/#an-ultimate-compilation-of-ai-resources-for-mathematics-machine-learning-and-deep-learning",
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"doc": "Resources",
"title": "Knowledge Not Shared is wasted. - Clan Jacobs",
"content": "This collection is a compilation of Excellent ML and DL Tutorials created by the people below . | Andrej Karpathy blog | Brandon Roher | Andrew Trask | Jay Alammar | Sebastian Ruder | Distill | StatQuest with Josh Starmer | sentdex | Lex Fridman | 3Blue1Brown | Alexander Amini | The Coding Train | Christopher Olah ",
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"relUrl": "/docs/customization/#knowledge-not-shared-is-wasted---clan-jacobs"
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"doc": "Resources",
"title": "Communities to Follow",
"content": "| AI Coimbatore Join here🔗⬇️ . | Telegram : For Daily Updates | Facebook : Coimbatore School of AI | . | TensorFlow User Group Coimbatore . | Meetup : TFUGCbe | Facebook : TFUGCbe | . | . ",
"url": "/docs/customization/#communities-to-follow",
"relUrl": "/docs/customization/#communities-to-follow"
- },"87": {
+ },"95": {
"doc": "Resources",
"title": "This Repo is Created and Maintained by",
"content": "Navaneeth Malingan . ",
"url": "/docs/customization/#this-repo-is-created-and-maintained-by",
"relUrl": "/docs/customization/#this-repo-is-created-and-maintained-by"
- },"88": {
+ },"96": {
"doc": "Resources",
"title": "Why Data Science and how to get started?",
"content": ". | 🖥️ HOW TO GET STARTED WITH MACHINE LEARNING! | How to Build a Meaningful Career in Data Science | My Self-Created Artificial Intelligence Masters Degree | PyImageSearch | 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python | . ",
"url": "/docs/customization/#why-data-science-and-how-to-get-started",
"relUrl": "/docs/customization/#why-data-science-and-how-to-get-started"
- },"89": {
+ },"97": {
"doc": "Resources",
"title": "Intro to ML",
"content": ". | Luis Serrano: A Friendly Introduction to Machine Learning | StatQuest: A Gentle Introduction to Machine Learning | Machine Learning For Everyone Summarize’s Machine Learning algorithms and their applications in simple words with real-world examples. | . ",
"url": "/docs/customization/#intro-to-ml",
"relUrl": "/docs/customization/#intro-to-ml"
- },"90": {
+ },"98": {
"doc": "Resources",
"title": "Anyone can do Machine Learning",
"content": ". | Teachable Machine Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required. | . ",
"url": "/docs/customization/#anyone-can-do-machine-learning",
"relUrl": "/docs/customization/#anyone-can-do-machine-learning"
- },"91": {
+ },"99": {
"doc": "Resources",
"title": "MOOCs",
"content": ". | Machine Learning by Andrew Ng, Stanford IMDB 10/10 LOL :P | Datacamp : Data Engineer with Python | Intro to Machine Learning Topics Covered Naive Bayes, SVM, Decision Trees, Regressions, Outliers, Clustering, Feature Scaling, Text Learning, Feature Selection, PCA, Validation, Evaluation Metrics | Intro to TensorFlow for Deep Learning The Best Course for Learning TensorFlow | End-to-End Machine Learning | NVIDIA DEEP LEARNING INSTITUTE | Introduction to Machine Learning for Coders! | Practical Deep Learning for Coders, v3 | FastAI | . ",
"url": "/docs/customization/#moocs",
"relUrl": "/docs/customization/#moocs"
- },"92": {
+ },"100": {
"doc": "Resources",
"title": "Courses from Top Universities",
"content": "### Stanford University . | CS221 - Artificial Intelligence: Principles and Techniques by Percy Liang and Dorsa Sadigh | CS229 - Machine Learning by Andrew Ng | CS230 - Deep Learning by Andrew Ng | CS231n - Convolutional Neural Networks for Visual Recognition by Fei-Fei Li and Andrej Karpathy | CS224n - Natural Language Processing with Deep Learning by Christopher Manning | CS234 - Reinforcement Learning by Emma Brunskill | CS330 - Deep Multi-task and Meta Learning by Chelsea Finn | CS25 - Transformers United | . ### Carnegie Mellon University . | CS/LTI 11-711: Advanced NLP by Graham Neubig | CS/LTI 11-747: Neural Networks for NLP by Graham Neubig | CS/LTI 11-737: Multilingual NLP by Graham Neubig | CS/LTI 11-777: Multimodal Machine Learning by Louis-Philippe Morency | CS/LTI 11-785: Introduction to Deep Learning by Bhiksha Raj and Rita Singh | CS/LTI Low Resource NLP Bootcamp 2020 by Graham Neubig | . ### Massachusetts Institute of Technology . | 6.S191 - Introduction to Deep Learning by Alexander Amini and Ava Amini | 6.S094 - Deep Learning by Lex Fridman | 6.S192 - Deep Learning for Art, Aesthetics, and Creativity by Ali Jahanian | . ### University College London . | COMP M050 Reinforcement Learning by David Silver | . ",
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"relUrl": "/docs/customization/#courses-from-top-universities"
- },"93": {
+ },"101": {
"doc": "Resources",
"title": "YouTube ML Playlists",
"content": ". | Machine Learning by StatQuest with Josh Starmer | Intelligence and Learning by The Coding Train | . ",
"url": "/docs/customization/#youtube-ml-playlists",
"relUrl": "/docs/customization/#youtube-ml-playlists"
- },"94": {
+ },"102": {
"doc": "Resources",
"title": "Machine Learning Glossary",
"content": ". | This glossary defines general machine learning terms in a variety of domains, as well as terms specific to TensorFlow. | . ",
"url": "/docs/customization/#machine-learning-glossary",
"relUrl": "/docs/customization/#machine-learning-glossary"
- },"95": {
+ },"103": {
"doc": "Resources",
"title": "Machine Learning Fundamentals (These terms will be often used in the below algorithms)",
"content": ". | Bias and Variance | Cross Validation | Machine Learning Fundamentals: The Confusion Matrix | Sensitivity and Specivicity | ROC and AUC, Clearly Explained! | StatQuest: R-squared explained | Regularization Part 1: Ridge Regression | Regularization Part 2: Lasso Regression | Maximum Likelihood | Covariance and Correlation Part 1: Covariance | Statistics Fundamentals: The Mean, Variance and Standard Deviation | Statistics Fundamentals: Population Parameters | Glossary: Statistics | Glossary: Machine Learning | Looking at R-Squared | . ",
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"relUrl": "/docs/customization/#machine-learning-fundamentals-these-terms-will-be-often-used-in-the-below-algorithms"
- },"96": {
+ },"104": {
"doc": "Resources",
"title": "Math",
"content": ". | Mathematics for Machine Learning In this post I have compiled great e-resources (MOOC, YouTube Lectures, Books) for learning Mathematics for Machine Learning. | Mathematics for Machine Learning - Book One great book for all things math for machine learning. (free eBook) | I highly Recommend you to go through the following resources by 3Blue1Brown . | Essence of Linear Algrbra▶️ | Essene of Calculus▶️ | Differential equations▶️ | . | Gilbert Strang: Linear Algebra vs Calculus▶️ | Basics of Integral Calculus in Tamil▶️ | New fast.ai course: Computational Linear Algebra | Linear Algebra Book | . ",
"url": "/docs/customization/#math",
"relUrl": "/docs/customization/#math"
- },"97": {
+ },"105": {
"doc": "Resources",
"title": "Python",
"content": ". | Python Programming Tutorials by Socratica▶️ | Python Tutorial by w3schools📙 | Learning Python Programming📙 | . ",
"url": "/docs/customization/#python",
"relUrl": "/docs/customization/#python"
- },"98": {
+ },"106": {
"doc": "Resources",
"title": "Numpy",
"content": ". | A Visual Intro to NumPy and Data Representation | CS231n : Python Numpy Tutorial | NumPy resources : part of the End-to-End Machine Learning library | 100 numpy exercises (with solutions) | 101 NumPy Exercises for Data Analysis (Python) | Numpy Tutorial – Introduction to ndarray | Sci-Py Lectures : NumPy: creating and manipulating numerical data | Python NumPy Tutorial for Beginners▶️ Learn the basics of the NumPy library in this tutorial for beginners. It provides background information on how NumPy works and how it compares to Python’s Built-in lists. This video goes through how to write code with NumPy. It starts with the basics of creating arrays and then gets into more advanced stuff. The video covers creating arrays, indexing, math, statistics, reshaping, and more. | Python NumPy Tutorial – Learn NumPy Arrays With Examples | Python Numpy Array Tutorial | NumPy Tutorial: Data analysis with Python | Deep Learning Prerequisites: The Numpy Stack in Python▶️ | . ",
"url": "/docs/customization/#numpy",
"relUrl": "/docs/customization/#numpy"
- },"99": {
+ },"107": {
"doc": "Resources",
"title": "Pandas",
"content": ". | A Gentle Visual Intro to Data Analysis in Python Using Pandas | Data analysis in Python with pandas by Data School▶️ | Best practices with pandas by Data School▶️ | Python Pandas Tutorial: A Complete Introduction for Beginners | . ",
"url": "/docs/customization/#pandas",
"relUrl": "/docs/customization/#pandas"
- },"100": {
+ },"108": {
"doc": "Resources",
"title": "Machine Learning YouTube Playlists",
"content": ". | CodeBasics: Machine Learning Tutorial Python▶️ | StatQuest: Machine Learning▶️ | sentdex: Machine Learning with Python▶️ | Simplilearn: Machine Learning Tutorial Videos▶️ | Machine Learning Tutorial in Python▶️ | deeplizard: Machine Learning & Deep Learning Fundamentals▶️ | . ",
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"relUrl": "/docs/customization/#machine-learning-youtube-playlists"
- },"101": {
+ },"109": {
"doc": "Resources",
"title": "ML, DL Visual Explainers",
"content": ". | MLU-EXPLAIN | CNN Explainer | . Note: Below you can find the best lectures for popular Machine Learning Algorithms . ",
"url": "/docs/customization/#ml-dl-visual-explainers",
"relUrl": "/docs/customization/#ml-dl-visual-explainers"
- },"102": {
+ },"110": {
"doc": "Resources",
"title": "Linear Regression",
"content": ". | Linear Regression: A friendly introduction by Luis Serrano▶️ | Statistics 101: Linear Regression, The Very Basics▶️ | Regression Line Fitting Playground | Regression Curve Fitting Playground | . ",
"url": "/docs/customization/#linear-regression",
"relUrl": "/docs/customization/#linear-regression"
- },"103": {
+ },"111": {
"doc": "Resources",
"title": "Logistic Regression",
"content": ". | [Linear Regression vs Logistic Regression | Data Science Training | Edureka](https://www.youtube.com/watch?v=OCwZyYH14uw)▶️ | . | Logistic Regression and the Perceptron Algorithm: A friendly introduction by Luis Serrano▶️ | . ",
"url": "/docs/customization/#logistic-regression",
"relUrl": "/docs/customization/#logistic-regression"
- },"104": {
+ },"112": {
"doc": "Resources",
"title": "Decision Tree",
"content": ". | StatQuest: Decision Trees▶️ | StatQuest: Decision Trees, Part 2 - Feature Selection and Missing Data▶️ | Decision Tree Introduction with example📙 | Decision Tree📙 | | [Python | Decision Tree Regression using sklearn](https://www.geeksforgeeks.org/python-decision-tree-regression-using-sklearn/)📙 | . | | [ML | Logistic Regression v/s Decision Tree Classification](https://www.geeksforgeeks.org/ml-logistic-regression-v-s-decision-tree-classification/)📙 | . | . ",
"url": "/docs/customization/#decision-tree",
"relUrl": "/docs/customization/#decision-tree"
- },"105": {
+ },"113": {
"doc": "Resources",
"title": "Random Forest",
"content": ". | StatQuest: Random Forests Part 1 - Building, Using and Evaluating▶️ | StatQuest: Random Forests Part 2: Missing data and clustering▶️ | Random Forests for Complete Beginners📙 | . ",
"url": "/docs/customization/#random-forest",
"relUrl": "/docs/customization/#random-forest"
- },"106": {
+ },"114": {
"doc": "Resources",
"title": "Boosting Machine Learning",
"content": ". | [Boosting Machine Learning Tutorial | Adaptive Boosting, Gradient Boosting, XGBoost | Edureka](https://www.youtube.com/watch?v=kho6oANGu_A)▶️ | . | AdaBoost, Clearly Explained▶️ | Gradient Boost Part 1: Regression Main Ideas▶️ | Gradient Boost Part 2: Regression Details▶️ | Gradient Boost Part 3: Classification▶️ | Gradient Boost Part 4: Classification Details▶️ | XGBoost Part1: XGBoost Trees for Regression▶️ | XGBoost Part 2: XGBoost Trees For Classification▶️ | Ensemble methods Sci-kit learn | . ",
"url": "/docs/customization/#boosting-machine-learning",
"relUrl": "/docs/customization/#boosting-machine-learning"
- },"107": {
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"doc": "Resources",
"title": "SVM",
"content": ". | Support Vector Machines (SVMs): A friendly introduction by Luis Serrano▶️ | Support Vector Machines, Clearly Explained!!! by StatQuest▶️ | Support Vector Machines Part 2: The Polynomial Kernel by StatQuest▶️ | Support Vector Machines Part 3: The Radial (RBF) Kernel by StatQuest▶️ | How Support Vector Machines work / How to open a black box▶️ | Support Vector Machines - The Math of Intelligence (Week 1)▶️ | Demystifying Support Vector Machines📙 | Support Vector Machine (SVM) - Fun and Easy Machine Learning▶️ | . ",
"url": "/docs/customization/#svm",
"relUrl": "/docs/customization/#svm"
- },"108": {
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"doc": "Resources",
"title": "Bayes Theorem",
"content": ". | Bayes theorem, and making probability intuitive▶️ | A friendly introduction to Bayes Theorem and Hidden Markov Models▶️ | The Bayesian Trap▶️ | Naive Bayes classifier: A friendly approach▶️ | . ",
"url": "/docs/customization/#bayes-theorem",
"relUrl": "/docs/customization/#bayes-theorem"
- },"109": {
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"doc": "Resources",
"title": "K-Nearest Neighbors",
"content": ". | KNN from Scratch📙 | Machine Learning Basics with the K-Nearest Neighbors Algorithm📙 | . ",
"url": "/docs/customization/#k-nearest-neighbors",
"relUrl": "/docs/customization/#k-nearest-neighbors"
- },"110": {
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"doc": "Resources",
"title": "K-Means",
"content": ". | StatQuest: K-means clustering▶️ | Machine Learning Tutorial Python - 13: K Means Clustering▶️ | K Means Clustering Algorithm - K Means Example in Python - Machine Learning Algorithms - Edureka▶️ | . ",
"url": "/docs/customization/#k-means",
"relUrl": "/docs/customization/#k-means"
- },"111": {
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"doc": "Resources",
"title": "Principal Component Analysis (PCA)",
"content": ". | StatQuest: PCA main ideas in only 5 minutes!!!▶️ | StatQuest: Principal Component Analysis (PCA), Step-by-Step▶️ | Principal Component Analysis (PCA) by Luis Serrano▶️ | . ",
"url": "/docs/customization/#principal-component-analysis-pca",
"relUrl": "/docs/customization/#principal-component-analysis-pca"
- },"112": {
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"doc": "Resources",
"title": "Probabilistic Graphical Models",
"content": ". | Probabilistic Graphical Models Specialization | . ",
"url": "/docs/customization/#probabilistic-graphical-models",
"relUrl": "/docs/customization/#probabilistic-graphical-models"
- },"113": {
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"doc": "Resources",
"title": "Gradient Descent from Scratch",
"content": "The Best . | Linear Regression using Gradient Descent📙 | Gradient Descent, Step-by-Step▶️ | Stochastic Gradient Descent, Clearly Explained!!!▶️ | How Optimization Works A short series on the fundamentals of optimization for machine learning | Linear Regression using Gradient Descent . | Code | . | Polynomial Regression | Gradient Descent in Linear Regression - Math📙 | Neural Network Backpropagation Basics For Dummies▶️ | . Extra Good Ones . | 3.4: Linear Regression with Gradient Descent - Intelligence and Learning▶️ | 3.5: Mathematics of Gradient Descent - Intelligence and Learning▶️ | 3.5a: Calculus: Power Rule - Intelligence and Learning▶️ | 3.5b: Calculus: Chain Rule - Intelligence and Learning▶️ | 3.5c: Calculus: Partial Derivative - Intelligence and Learning▶️ | . Vanishing Gradient . | Vanishing Gradient Problem▶️ | How to overcome Vanishing Gradient Problem▶️ | . How to Handle Local Minima . | https://datascience.stackexchange.com/questions/24534/does-gradient-descent-always-converge-to-an-optimum | https://datascience.stackexchange.com/questions/18802/does-mlp-always-find-local-minimum | https://www.coursera.org/learn/deep-neural-network/lecture/RFANA/the-problem-of-local-optima | . ",
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"relUrl": "/docs/customization/#gradient-descent-from-scratch"
- },"114": {
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"doc": "Resources",
"title": "Scikit-learn",
"content": ". | An introduction to machine learning with scikit-learn📙 | Python Machine Learning: Scikit-Learn Tutorial | . ",
"url": "/docs/customization/#scikit-learn",
"relUrl": "/docs/customization/#scikit-learn"
- },"115": {
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"doc": "Resources",
"title": "Deep Learning",
"content": ". | DEEP BLUEBERRY BOOK This is a tiny and very focused collection of links about deep learning. If you’ve always wanted to learn deep learning stuff but don’t know where to start, you might have stumbled upon the right place! | 6.S191: Introduction to Deep Learning (2019) . | Class Lectures (YouTube) - MIT 6.S191: Introduction to Deep Learning | Lab | . | MIT 6.S191 Introduction to Deep Learning (2020) | MIT 6.S191 Introduction to Deep Learning (2023) (YouTube) | MIT Deep Learning Basics: Introduction and Overview | MIT Deep Learning by Lex Fridman . | Deep Learning Lectures (YouTube) | . | Deep Learning in Tamil | . Deep Leraning Books . | The Deep Learning Textbook from Ian Goodfellow, Yoshua Bengio, and Aaron Courville | Neural Networks And Deep Learning by Michael Nielsen | Grokking Deep Learning by Andrew Trask | . Deep Lerning Papers . | Deep Learning Papers Reading Roadmap | . ",
"url": "/docs/customization/#deep-learning",
"relUrl": "/docs/customization/#deep-learning"
- },"116": {
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"doc": "Resources",
"title": "NN",
"content": ". | A friendly introduction to Deep Learning and Neural Networks▶️ | Machine Learning for Beginners: An Introduction to Neural Networks📙 A simple explanation of how they work and how to implement one from scratch in Python. | A Visual and Interactive Guide to the Basics of Neural Networks📙 | A Visual And Interactive Look at Basic Neural Network Math📙 | Neural Network Architectures▶️ | Neural Networks Demystified by Welch Labs▶️ . | Supporting code for short YouTube series Neural Networks Demystified. | . | Neural networks Series by 3Blue1Brows▶️ | . ",
"url": "/docs/customization/#nn",
"relUrl": "/docs/customization/#nn"
- },"117": {
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"doc": "Resources",
"title": "Computer Vision",
"content": ". | CS131 Computer Vision: Foundations and Applications Fall 2019 | CS231A: Computer Vision, From 3D Reconstruction to Recognition Winter 2018 | CS231n Convolutional Neural Networks for Visual Recognition | . CNN . | CS231n: Convolutional Neural Networks for Visual Recognition Spring 2019 | CS231n: Convolutional Neural Networks for Visual Recognition | A friendly introduction to Convolutional Neural Networks and Image Recognition | A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way | Tensorflow Convolutional Neural Network (CNN) | Convolutional Networks Book | CNNs, Part 1: An Introduction to Convolutional Neural Networks | CS231n Winter 2016 BY Andrej Karpathy 15 Videos | Intuitive understanding of 1D, 2D, and 3D Convolutions in Convolutional Neural Networks | CNN ExplainerAn interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs) | . Object Detection . Evolution Of Object Detection Networks by Cogneethi . Deep-dive tutorial on Object Detection. Intuition lectures on topics ranging from Classical CV techniques like HOG, SIFT to Convolutional Neural Network based techniques like Overfeat, Faster RCNN etc. You will learn how the ideas have evolved from some of the earliest papers to current ones. And hence the name Evolution of Object Detection Networks. | [SIFT | Scale Invariant Feature Transform](https://www.youtube.com/watch?v=ttD3pvM6pEI&list=PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S&index=19&ab_channel=Cogneethi) | . | | [Hog Intuition | Histogram of Oriented Gradients](https://www.youtube.com/watch?v=Qwc3a8cOKRU&list=PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S&index=20&ab_channel=Cogneethi) | . | | [NMS | Non Max Suppression](https://www.youtube.com/watch?v=07jFApuhh4I&list=PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S&index=25&ab_channel=Cogneethi) | . | | [Object Localization | Bounding Box Regression](https://www.youtube.com/watch?v=LZRfHkTNQqo&list=PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S&index=49&ab_channel=Cogneethi) | . | Object Detection | RCNN | | [Spatial Pyramid Matching | SPM](https://www.youtube.com/watch?v=6MwuK2wHlOg&list=PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S&index=70&t=92s&ab_channel=Cogneethi) | . | SPPNet Object Detection | Fast RCNN Network | Faster RCNN | Yolo v4 Object Detection - How it Works & Why it’s So Amazing! | Frameworks and Libraries . | Detectron2 by Facebook AI | MMDetection | MediaPipe | YOLO | TensorFlow Object Detection API | Computer Vision Recipes | . | Labeling Tools . | LabelImg | Roboflow | Label Studio | . | Code samples . | YOLO-Object-Counting-API | . | . 3D Object Detection . | [Announcing the Objectron Dataset | Google AI Blog](https://ai.googleblog.com/2020/11/announcing-objectron-dataset.html) | . | | [MediaPipe Objectron | Objectron (3D Object Detection)](https://google.github.io/mediapipe/solutions/objectron.html) | . | . Image Segmentation . | Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques (Part 1) | . GANs . | A Friendly Introduction to Generative Adversarial Networks (GANs) by Luis Serrano | Generative Adversarial Networks (GANs) by Ahlad Kumar | Building our first simple GAN | Face editing with Generative Adversarial Networks | Variational Autoencoders | Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch) | Generative Models | . Style Transfer . | TensorFlow CNN for fast style transfer ⚡🖥🎨🖼 | . ",
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- },"118": {
+ },"126": {
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"content": ". | CS224n: Natural Language Processing with Deep Learning | NLP and The Reformer | The Illustrated Word2vec | . RNN . | Illustrated Guide to Recurrent Neural Networks: Understanding the Intuition | Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN) Baby steps to your neural network’s first memories. | The Unreasonable Effectiveness of Recurrent Neural Networks | An Introduction to Recurrent Neural Networks for Beginners A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python. | Attention and Augmented Recurrent Neural Networks by Distill | Visualizing memorization in RNNs by Distill Inspecting gradient magnitudes in context can be a powerful tool to see when recurrent units use short-term or long-term contextual understanding. | Deep Learning for NLP: ANNs, RNNs and LSTMs explained! | . LSTM . | Understanding LSTM Networks | LSTM implementation explained | A Gentle Introduction to LSTM Autoencoders | . Transformers and Self Attention . Visual Guide to Transformer Neural Networks (Highly Recommended) . | Part 1 - Position Embeddings | Part 2 - Multi-Head & Self Attention | Part 3 - Decoder’s Masked Attention | NLP Transformers Attention Playlist | The Illustrated Transformer | The Annotated Transformer | Transformers Paper and Code | Transformers from Scratch | Transformers Notes | Transformers, Explained: Understand the Model Behind GPT-3, BERT, and T5 | A comprehensive overview of Transformer variants. | How to become an NLP & Transformer Model Guru | [MASTERCLASS] Transformers | Attention Models BERT . | Explaining BERT Simply Using Sketches | A Visual Guide to Using BERT for the First Time | The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) | BERT Explained: State of the art language model for NLP | BioBERT, a language representation model for biomedical domain, especially designed for biomedical text mining tasks such as biomedical named entity recognition, relation extraction, question answering, etc | . GPT . | The Illustrated GPT-2 (Visualizing Transformer Language Models) | . ",
"url": "/docs/customization/#nlp",
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- },"119": {
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"title": "Reinforcement Learning",
"content": ". | Deep Reinforcement Learning Course 🕹️ A Free course in Deep Reinforcement Learning from beginner to expert. | Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton’s Book and David Silver’s course. | Unity Machine Learning Agents Toolkit | 🖥️ WRITING MY FIRST MACHINE LEARNING GAME! (1/4) | Deep Reinforcement Learning: Pong from Pixels by Andrej Karpathy | A Beginner’s Guide to Deep Reinforcement Learning | An Introduction to Unity ML-Agents | Deep Reinforcement Learning Algorithms with PyTorch | LECTURES: Introduction to Reinforcement Learning - David Silver | BOOK: Reinforcement Learning - An Introduction by Sutton and Barto | BOOK: Deep Reinforcement Learning Hands On by Maxim Lapan | . ",
"url": "/docs/customization/#reinforcement-learning",
"relUrl": "/docs/customization/#reinforcement-learning"
- },"120": {
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"content": ". | Udacity : Deep Learning with PyTorch | Deep Learning (PyTorch) : Code | Udacity : Secure AI | TORCHSCRIPT | PyTorchZeroToAll (in English) Sung Kim a Series of 14 Videos . | Supporting Code | Slides | . | . ",
"url": "/docs/customization/#pytorch",
"relUrl": "/docs/customization/#pytorch"
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"content": ". | Introduction to TensorFlow 2.0: Easier for beginners, and more powerful for experts (TF World ‘19) | TensorFlow Lite: Solution for running ML on-device (TF World ‘19) | Machine Learning in JavaScript (TensorFlow Dev Summit 2018) | TensorFlow.js Quick Start | Keras vs. tf.keras: What’s the difference in TensorFlow 2.0? | How To Run TensorFlow Lite on Raspberry Pi for Object Detection | | [How computers learn to recognize objects instantly | Joseph Redmon](https://www.youtube.com/watch?v=Cgxsv1riJhI) | . | . TensorFlow Courses . | Intro to TensorFlow for Deep Learning | TensorFlow in Practice Specialization : Coursera | TensorFlow: Data and Deployment Specialization : Coursera | . PyTorch Vs TensorFlow . | Why is PyTorch becoming so popular among machine learning engineers? | . ",
"url": "/docs/customization/#tensorflow",
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"content": ". | Transfer Learning with Keras and Deep Learning | A Comprehensive Hands-on Guide to Transfer Learning with Real-World Applications in Deep Learning | TensorFlow Core Tutorials | . ",
"url": "/docs/customization/#transfer-learning",
"relUrl": "/docs/customization/#transfer-learning"
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"title": "Deploy Models",
"content": ". | Machine Learning in 5 Minutes: How to deploy a ML model (SurveyMonkey Engineer explains) | Deploy Machine Learning Models with Django | MlFlow - An open source platform for the machine learning lifecycle | TensorFlow: Data and Deployment Specialization | . ",
"url": "/docs/customization/#deploy-models",
"relUrl": "/docs/customization/#deploy-models"
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"doc": "Resources",
"title": "MlOps",
"content": ". | MLOps Primer - 2021 A collection of resources to learn about MLOps. ",
"url": "/docs/customization/#mlops",
"relUrl": "/docs/customization/#mlops"
- },"125": {
+ },"133": {
"doc": "Resources",
"title": "Code",
"content": "| codebasics/py | Google Codelabs | . ",
"url": "/docs/customization/#code",
"relUrl": "/docs/customization/#code"
- },"126": {
+ },"134": {
"doc": "Resources",
"title": "CheatSheets",
"content": ". | Artificial Intelligence | Machine Learning | Deep Learning | Machine Learning tips and tricks | Data Science Tools | Machine Learning with R | CHRIS ALBON Cheat Sheets and Flash Cards | MLOps Tooling Landscape v2 (+84 new tools) - Dec ‘20 | Mathematical tools | Ordinary Differential Equations for Engineers | . ",
"url": "/docs/customization/#cheatsheets",
"relUrl": "/docs/customization/#cheatsheets"
- },"127": {
+ },"135": {
"doc": "Resources",
"title": "Edge ML Kits",
"content": ". | Nvidia Jetson Nano Developer Kit | Intel® Neural Compute Stick 2 (Intel® NCS2) | Coral | . ",
"url": "/docs/customization/#edge-ml-kits",
"relUrl": "/docs/customization/#edge-ml-kits"
- },"128": {
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"doc": "Resources",
"title": "Data Science Competitions",
"content": ". | Kaggle | . ",
"url": "/docs/customization/#data-science-competitions",
"relUrl": "/docs/customization/#data-science-competitions"
- },"129": {
+ },"137": {
"doc": "Resources",
"title": "Important Youtube🎬 Channels in the field of AI/ML/RL/DS",
"content": ". | 3Blue1Brown | StatQuest with Josh Starmer | Sentdex | Luis Serrano | Brandon Rohrer | deeplizard | Tech With Tim | Microsoft Research | Corey Schafer | Data School | Two Minute Papers | Welch Labs | Simplilearn | Great Learning | DeepLearning.TV | TensorFlow | Deeplearning.ai | Code Bullet | edureka! | Lex Fridman | The Artificial Intelligence Channel | freeCodeCamp.org | CloudxLab | Alexander Amini | Jeff Heaton | Abhishek Thakur | The Coding Train | . ",
"url": "/docs/customization/#important-youtube-channels-in-the-field-of-aimlrlds",
"relUrl": "/docs/customization/#important-youtube-channels-in-the-field-of-aimlrlds"
- },"130": {
+ },"138": {
"doc": "Resources",
"title": "Reference",
"content": ". | 🖥️ HOW TO GET STARTED WITH MACHINE LEARNING! | My Self-Created Artificial Intelligence Masters Degree | https://end-to-end-machine-learning.teachable.com/courses/667372/lectures/11900568 | ML Fundamentals by StatQuest | Machine Learning with Python by sentdex | 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python - Daniel Bourke | Data School | Neural Networks and Deep Learning | https://www.machinelearningisfun.com/ | https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471 | https://medium.com/greyatom | https://greyatom.com/glabs | | [John Searle: “Consciousness in Artificial Intelligence” | Talks at Google](https://www.youtube.com/watch?v=rHKwIYsPXLg) | . | https://github.com/nature-of-code/NOC-S17-2-Intelligence-Learning/tree/master/week3-classification-regression | https://github.com/nature-of-code/NOC-S17-2-Intelligence-Learning | . ",
"url": "/docs/customization/#reference",
"relUrl": "/docs/customization/#reference"
- },"131": {
+ },"139": {
"doc": "Resources",
"title": "Resources",
"content": " ",
"url": "/docs/customization/",
"relUrl": "/docs/customization/"
- },"132": {
+ },"140": {
"doc": "Default layout child page",
"title": "Default layout child page",
"content": "This is a child page that uses the same minimal layout as its parent page. ",
"url": "/docs/layout/minimal/default-child/",
"relUrl": "/docs/layout/minimal/default-child/"
- },"133": {
- "doc": "Projects",
- "title": "Projects",
+ },"141": {
+ "doc": "Final Year Project Generator",
+ "title": "Final Year Project Generator",
"content": " ",
- "url": "/docs/index-test/",
-
- "relUrl": "/docs/index-test/"
- },"134": {
- "doc": "Projects",
- "title": "1. Project Awadhi",
- "content": "This project focuses on developing localized solutions using advanced AI and machine learning techniques. ",
- "url": "/docs/index-test/#1-project-awadhi",
+ "url": "/docs/layout/projects/final_year_project/",
- "relUrl": "/docs/index-test/#1-project-awadhi"
- },"135": {
- "doc": "Projects",
- "title": "2. Lallan",
- "content": ". | Lallan - Lucknow Artificial Language and Learning Assistance Network | . Try Lallan . ",
- "url": "/docs/index-test/#2-lallan",
-
- "relUrl": "/docs/index-test/#2-lallan"
- },"136": {
- "doc": "Projects",
- "title": "3. Project Sign Language",
- "content": "This project focuses on developing localized solutions using advanced AI and machine learning techniques. ",
- "url": "/docs/index-test/#3-project-sign-language",
-
- "relUrl": "/docs/index-test/#3-project-sign-language"
- },"137": {
+ "relUrl": "/docs/layout/projects/final_year_project/"
+ },"142": {
"doc": "Home",
"title": "Lucknow AI Labs",
"content": "Open Source AI Research & Mentorship . Get started now Try Lucknow-GPT . Contributing . When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change. Read more about becoming a contributor in our GitHub repo. Thank you to the contributors of Lucknow AI! . | | | | . Code of Conduct . Lucknow AI is committed to fostering a welcoming community. View our Code of Conduct on our GitHub repository. Source: https://gdglucknow.web.app ",
"url": "/#lucknow-ai-labs",
"relUrl": "/#lucknow-ai-labs"
- },"138": {
+ },"143": {
"doc": "Home",
"title": "Home",
"content": "Change Theme . ",
"url": "/",
"relUrl": "/"
- },"139": {
+ },"144": {
"doc": "Labels",
"title": "Labels",
"content": "Use labels as a way to add an additional mark to a section of your docs. Labels come in a few colors. By default, labels will be blue. Default label . Blue label . Stable . New release . Coming soon . Deprecated . Default label {: .label } Blue label {: .label .label-blue } Stable {: .label .label-green } New release {: .label .label-purple } Coming soon {: .label .label-yellow } Deprecated {: .label .label-red } . ",
"url": "/docs/ui-components/labels/",
"relUrl": "/docs/ui-components/labels/"
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- "doc": "Lallan",
- "title": "Lallan",
- "content": " ",
- "url": "/projects/lallan/",
-
- "relUrl": "/projects/lallan/"
- },"141": {
- "doc": "Lallan",
- "title": "Lallan UI",
- "content": " ",
- "url": "/projects/lallan/#lallan-ui",
-
- "relUrl": "/projects/lallan/#lallan-ui"
- },"142": {
- "doc": "Lallan",
- "title": "About Lallan",
- "content": "| Collected and contributed unstructured data for the Lucknow Large Language Model (LLM) project. | Utilized contextual embeddings to enhance semantic search and retrieval capabilities. | Integrated Google's state-of-the-art Gemini LLM for extracting answers along with embedded context from local data sources. | Implemented FastAPI backend services to support the deployment of the Retrieval-Augmented Generation (RAG) system. | Integrated FastAPI with Gradio to create an intuitive and user-friendly UI for the chatbot, improving accessibility and ease of use. | | | ",
- "url": "/projects/lallan/#about-lallan",
-
- "relUrl": "/projects/lallan/#about-lallan"
- },"143": {
+ },"145": {
"doc": "Events & Meetups",
"title": "Events & Meetups",
"content": " ",
- "url": "/docs/layout/layout/",
+ "url": "/docs/layout/Events%20&%20Meetups/layout/",
- "relUrl": "/docs/layout/layout/"
- },"144": {
+ "relUrl": "/docs/layout/Events%20&%20Meetups/layout/"
+ },"146": {
"doc": "Events & Meetups",
"title": "Layout Utilities",
"content": " ",
"url": "/docs/utilities/layout/#layout-utilities",
"relUrl": "/docs/utilities/layout/#layout-utilities"
- },"145": {
+ },"147": {
"doc": "Events & Meetups",
"title": "Table of contents",
"content": ". | Spacing | Horizontal Alignment | Vertical Alignment | Display | . ",
"url": "/docs/utilities/layout/#table-of-contents",
"relUrl": "/docs/utilities/layout/#table-of-contents"
- },"146": {
+ },"148": {
"doc": "Events & Meetups",
"title": "Spacing",
"content": "These spacers are available to use for margins and padding with responsive utility classes. Combine these prefixes with a screen size and spacing scale to use them responsively. | Classname prefix | What it does | . | .m- | margin | . | .mx- | margin-left, margin-right | . | .my- | margin top, margin bottom | . | .mt- | margin-top | . | .mr- | margin-right | . | .mb- | margin-bottom | . | .ml- | margin-left | . | Classname prefix | What it does | . | .p- | padding | . | .px- | padding-left, padding-right | . | .py- | padding top, padding bottom | . | .pt- | padding-top | . | .pr- | padding-right | . | .pb- | padding-bottom | . | .pl- | padding-left | . Spacing values are based on a 1rem = 16px spacing scale, broken down into these units: . | Spacer/suffix | Size in rems | Rem converted to px | . | 1 | 0.25rem | 4px | . | 2 | 0.5rem | 8px | . | 3 | 0.75rem | 12px | . | 4 | 1rem | 16px | . | 5 | 1.5rem | 24px | . | 6 | 2rem | 32px | . | 7 | 2.5rem | 40px | . | 8 | 3rem | 48px | . | auto | auto | auto | . Use mx-auto to horizontally center elements. Examples . In Markdown, use the {: } wrapper to apply custom classes: . This paragraph will have a margin bottom of 1rem/16px on large screens. {: .mb-lg-4 } This paragraph will have 2rem/32px of padding on the right and left at all screen sizes. {: .px-6 } . ",
"url": "/docs/utilities/layout/#spacing",
"relUrl": "/docs/utilities/layout/#spacing"
- },"147": {
+ },"149": {
"doc": "Events & Meetups",
"title": "Horizontal Alignment",
"content": "| Classname | What it does | . | .float-left | float: left | . | .float-right | float: right | . | .flex-justify-start | justify-content: flex-start | . | .flex-justify-end | justify-content: flex-end | . | .flex-justify-between | justify-content: space-between | . | .flex-justify-around | justify-content: space-around | . Note: any of the flex- classes must be used on a parent element that has d-flex applied to it. ",
"url": "/docs/utilities/layout/#horizontal-alignment",
"relUrl": "/docs/utilities/layout/#horizontal-alignment"
- },"148": {
+ },"150": {
"doc": "Events & Meetups",
"title": "Vertical Alignment",
"content": "| Classname | What it does | . | .v-align-baseline | vertical-align: baseline | . | .v-align-bottom | vertical-align: bottom | . | .v-align-middle | vertical-align: middle | . | .v-align-text-bottom | vertical-align: text-bottom | . | .v-align-text-top | vertical-align: text-top | . | .v-align-top | vertical-align: top | . ",
"url": "/docs/utilities/layout/#vertical-alignment",
"relUrl": "/docs/utilities/layout/#vertical-alignment"
- },"149": {
+ },"151": {
"doc": "Events & Meetups",
"title": "Display",
"content": "Display classes aid in adapting the layout of the elements on a page: . | Class | | . | .d-block | display: block | . | .d-flex | display: flex | . | .d-inline | display: inline | . | .d-inline-block | display: inline-block | . | .d-none | display: none | . Use these classes in conjunction with the responsive modifiers. Examples . In Markdown, use the {: } wrapper to apply custom classes: . This button will be hidden until medium screen sizes: [ A button ](#url) {: .d-none .d-md-inline-block } These headings will be `inline-block`: ### heading 3 {: .d-inline-block } ### heading 3 {: .d-inline-block } . ",
"url": "/docs/utilities/layout/#display",
"relUrl": "/docs/utilities/layout/#display"
- },"150": {
+ },"152": {
"doc": "Events & Meetups",
"title": "Events & Meetups",
"content": " ",
"url": "/docs/utilities/layout/",
"relUrl": "/docs/utilities/layout/"
- },"151": {
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"doc": "Code with line numbers",
"title": "Code snippets with line numbers",
"content": "The default settings for HTML compression are incompatible with the HTML produced by Jekyll (4.1.1 or earlier) for line numbers from highlighted code – both when using Kramdown code fences and when using Liquid highlight tags. To avoid non-conforming HTML and unsatisfactory layout, HTML compression can be turned off by using the following configuration option: . compress_html: ignore: envs: all . When using Kramdown code fences, line numbers are turned on globally by the following configuration option: . kramdown: syntax_highlighter_opts: block: line_numbers: true . Line numbers can then be suppressed locally using Liquid tags (without the linenos option) instead of fences: . {% highlight some_language %} Some code {% endhighlight %} . ",
"url": "/docs/ui-components/code/line-numbers/#code-snippets-with-line-numbers",
"relUrl": "/docs/ui-components/code/line-numbers/#code-snippets-with-line-numbers"
- },"152": {
+ },"154": {
"doc": "Code with line numbers",
"title": "Workarounds",
"content": "To use HTML compression together with line numbers, all highlighted code needs to be wrapped using one of the following workarounds. (The variable name some_var can be changed to avoid clashes; it can also be replaced by code – but note that code=code cannot be removed). Code fences (three backticks) . {% capture some_var %} ```some_language Some code ``` {% endcapture %} {% assign some_var = some_var | markdownify %} {% include fix_linenos.html code=some_var %} . Liquid highlighting . {% capture some_var %} {% highlight some_language linenos %} Some code {% endhighlight %} {% endcapture %} {% include fix_linenos.html code=some_var %} . Credit: The original version of the above workaround was suggested by Dmitry Hrabrov at https://github.com/penibelst/jekyll-compress-html/issues/71#issuecomment-188144901. ",
"url": "/docs/ui-components/code/line-numbers/#workarounds",
"relUrl": "/docs/ui-components/code/line-numbers/#workarounds"
- },"153": {
+ },"155": {
"doc": "Code with line numbers",
"title": "Examples",
"content": "✅ Using code fences + workaround (will only show line numbers if enabled globally in _config.yml): . // Javascript code with syntax highlighting in fences var fun = function lang(l) { dateformat.i18n = require('./lang/' + l) return true; } . ✅ Using liquid highlighting + workaround: . | 1 2 3 4 . | # Ruby code with syntax highlighting and fixed line numbers using Liquid GitHubPages::Dependencies.gems.each do |gem, version| s.add_dependency(gem, \"= #{version}\") end . | . Narrow code stays close to the line numbers: . | 1 2 3 . | def foo puts 'foo' end . | . The following generates incorrect and invalid HTML. It should not be used as a positive example; the improper layout (with the broken HTML tags) is intentional. ❌ With the compression options used for the theme docs, the following example illustrates the incorrect formatting arising from the incompatibility of HTML compression and the non-conforming HTML produced by Jekyll for line numbers: . | 1 2 3 . | def foo puts 'foo' end . | . ",
"url": "/docs/ui-components/code/line-numbers/#examples",
"relUrl": "/docs/ui-components/code/line-numbers/#examples"
- },"154": {
+ },"156": {
"doc": "Code with line numbers",
"title": "Code with line numbers",
"content": " ",
"url": "/docs/ui-components/code/line-numbers/",
"relUrl": "/docs/ui-components/code/line-numbers/"
- },"155": {
+ },"157": {
"doc": "Lists",
"title": "Lists",
"content": " ",
"url": "/docs/ui-components/lists/",
"relUrl": "/docs/ui-components/lists/"
- },"156": {
+ },"158": {
"doc": "Lists",
"title": "Table of contents",
"content": ". | Unordered list | Ordered list | Task list | Definition list | . Most lists can be rendered with pure Markdown. ",
"url": "/docs/ui-components/lists/#table-of-contents",
"relUrl": "/docs/ui-components/lists/#table-of-contents"
- },"157": {
+ },"159": {
"doc": "Lists",
"title": "Unordered list",
"content": ". | Item 1 | Item 2 | Item 3 | . or . | Item 1 | Item 2 | Item 3 | . - Item 1 - Item 2 - Item 3 _or_ * Item 1 * Item 2 * Item 3 . ",
"url": "/docs/ui-components/lists/#unordered-list",
"relUrl": "/docs/ui-components/lists/#unordered-list"
- },"158": {
+ },"160": {
"doc": "Lists",
"title": "Ordered list",
"content": ". | Item 1 | Item 2 | Item 3 | . 1. Item 1 1. Item 2 1. Item 3 . ",
"url": "/docs/ui-components/lists/#ordered-list",
"relUrl": "/docs/ui-components/lists/#ordered-list"
- },"159": {
+ },"161": {
"doc": "Lists",
"title": "Task list",
"content": ". | hello, this is a todo item | hello, this is another todo item | goodbye, this item is done | . - [ ] hello, this is a todo item - [ ] hello, this is another todo item - [x] goodbye, this item is done . ",
"url": "/docs/ui-components/lists/#task-list",
"relUrl": "/docs/ui-components/lists/#task-list"
- },"160": {
+ },"162": {
"doc": "Lists",
"title": "Definition list",
"content": "Definition lists require HTML syntax and aren’t supported with the GitHub Flavored Markdown compiler. Name Godzilla Born 1952 Birthplace Japan Color Green <dl> <dt>Name</dt> <dd>Godzilla</dd> <dt>Born</dt> <dd>1952</dd> <dt>Birthplace</dt> <dd>Japan</dd> <dt>Color</dt> <dd>Green</dd> </dl> . ",
"url": "/docs/ui-components/lists/#definition-list",
"relUrl": "/docs/ui-components/lists/#definition-list"
- },"161": {
+ },"163": {
"doc": "Minimal layout child page",
"title": "Minimal layout child page",
"content": "This is a child page that uses the same minimal layout as its parent page. ",
"url": "/docs/layout/minimal/minimal-child/",
"relUrl": "/docs/layout/minimal/minimal-child/"
- },"162": {
+ },"164": {
"doc": "Minimal layout test",
"title": "Minimal layout test",
"content": "Return to main website. This page demonstrates the packaged minimal layout, which does not render the sidebar or header. It can be used for standalone pages. It is also an example of using the new modular site components to define custom layouts; see “Custom layouts and includes” in the customization docs for more information. ",
"url": "/docs/minimal-test/",
"relUrl": "/docs/minimal-test/"
- },"163": {
+ },"165": {
"doc": "A minimal layout page",
"title": "A minimal layout page",
"content": "This page illustrates the built-in layout minimal. One of its child pages also uses the minimal layout; the other child pages uses the default layout. ",
"url": "/docs/layout/minimal/minimal/",
"relUrl": "/docs/layout/minimal/minimal/"
- },"164": {
+ },"166": {
+ "doc": "NAWAB AI",
+ "title": "Nawab AI",
+ "content": " ",
+ "url": "/docs/layout/projects/nawabAI/#nawab-ai",
+
+ "relUrl": "/docs/layout/projects/nawabAI/#nawab-ai"
+ },"167": {
+ "doc": "NAWAB AI",
+ "title": "Nawab AI",
+ "content": " ",
+ "url": "/docs/layout/projects/nawabAI/#nawab-ai-1",
+
+ "relUrl": "/docs/layout/projects/nawabAI/#nawab-ai-1"
+ },"168": {
+ "doc": "NAWAB AI",
+ "title": "NAWAB AI",
+ "content": " ",
+ "url": "/docs/layout/projects/nawabAI/",
+
+ "relUrl": "/docs/layout/projects/nawabAI/"
+ },"169": {
+ "doc": "Projects",
+ "title": "Community Projects",
+ "content": " ",
+ "url": "/docs/layout/projects/projects/#community-projects",
+
+ "relUrl": "/docs/layout/projects/projects/#community-projects"
+ },"170": {
+ "doc": "Projects",
+ "title": "Completed Projects",
+ "content": "Currently, there are no completed projects to showcase. ",
+ "url": "/docs/layout/projects/projects/#completed-projects",
+
+ "relUrl": "/docs/layout/projects/projects/#completed-projects"
+ },"171": {
+ "doc": "Projects",
+ "title": "Ongoing Projects",
+ "content": "| Project Name | Description | . | NAWAB AI | An application for the people of Lucknow where they can find news, map locations, and a personalized chat assistant to guide them in the city. | . | Final Year Project Generator | A tool for students in their final year of college, helping them generate and refine ideas for their final year projects. | . ",
+ "url": "/docs/layout/projects/projects/#ongoing-projects",
+
+ "relUrl": "/docs/layout/projects/projects/#ongoing-projects"
+ },"172": {
+ "doc": "Projects",
+ "title": "Projects",
+ "content": " ",
+ "url": "/docs/layout/projects/projects/",
+
+ "relUrl": "/docs/layout/projects/projects/"
+ },"173": {
"doc": "Responsive Modifiers",
"title": "Responsive modifiers",
"content": "Just the Docs spacing works in conjunction with a variety of modifiers that allow you to target specific screen sizes responsively. Use these in conjunction with spacing and display prefix and suffix classes. | Modifier | Screen size | . | (none) | All screens until the next modifier | . | xs | 320px (20rem) and up | . | sm | 500px (31.25rem) and up | . | md | 740px (46.25rem) and up | . | lg | 1120px (70rem) and up | . | xl | 1400px (87.5rem) and up | . ",
"url": "/docs/utilities/responsive-modifiers/#responsive-modifiers",
"relUrl": "/docs/utilities/responsive-modifiers/#responsive-modifiers"
- },"165": {
+ },"174": {
"doc": "Responsive Modifiers",
"title": "Responsive Modifiers",
"content": " ",
"url": "/docs/utilities/responsive-modifiers/",
"relUrl": "/docs/utilities/responsive-modifiers/"
- },"166": {
+ },"175": {
"doc": "Tables",
"title": "Tables",
"content": "Tables are responsive by default, allowing wide tables to have a horizontal scroll to access columns outside of the normal viewport. | head1 | head two | three | . | ok | good swedish fish | nice | . | out of stock | good and plenty | nice | . | ok | good oreos | hmm | . | ok | good zoute drop | yumm | . | head1 | head two | three |:-------------|:------------------|:------| ok | good swedish fish | nice | out of stock | good and plenty | nice | ok | good `oreos` | hmm | ok | good `zoute` drop | yumm | . ",
"url": "/docs/ui-components/tables/",
"relUrl": "/docs/ui-components/tables/"
- },"167": {
+ },"176": {
"doc": "Typography",
"title": "Typography",
"content": " ",
"url": "/docs/ui-components/typography/",
"relUrl": "/docs/ui-components/typography/"
- },"168": {
+ },"177": {
"doc": "Typography",
"title": "Table of contents",
"content": ". | Font stack | Responsive type scale | Headings | Body text | Inline elements | Typographic Utilities | . ",
"url": "/docs/ui-components/typography/#table-of-contents",
"relUrl": "/docs/ui-components/typography/#table-of-contents"
- },"169": {
+ },"178": {
"doc": "Typography",
"title": "Font stack",
"content": "By default, Just the Docs uses a native system font stack for sans-serif fonts: . system-ui, -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, \"Helvetica Neue\", Arial, sans-serif, \"Segoe UI Emoji\" . ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz . For monospace type, like code snippets or the <pre> element, Just the Docs uses a native system font stack for monospace fonts: . \"SFMono-Regular\", Menlo, Consolas, Monospace . ABCDEFGHIJKLMNOPQRSTUVWXYZ abcdefghijklmnopqrstuvwxyz . ",
"url": "/docs/ui-components/typography/#font-stack",
"relUrl": "/docs/ui-components/typography/#font-stack"
- },"170": {
+ },"179": {
"doc": "Typography",
"title": "Responsive type scale",
"content": "Just the Docs uses a responsive type scale that shifts depending on the viewport size. | Selector | Small screen size font-size | Large screen size font-size | . | h1, .text-alpha | 32px | 36px | . | h2, .text-beta | 18px | 24px | . | h3, .text-gamma | 16px | 18px | . | h4, .text-delta | 14px | 16px | . | h5, .text-epsilon | 16px | 18px | . | h6, .text-zeta | 18px | 24px | . | body | 14px | 16px | . ",
"url": "/docs/ui-components/typography/#responsive-type-scale",
"relUrl": "/docs/ui-components/typography/#responsive-type-scale"
- },"171": {
+ },"180": {
"doc": "Typography",
"title": "Headings",
"content": "Headings are rendered like this: . ",
"url": "/docs/ui-components/typography/#headings",
"relUrl": "/docs/ui-components/typography/#headings"
- },"172": {
+ },"181": {
"doc": "Typography",
"title": "Heading 1",
"content": " ",
"url": "/docs/ui-components/typography/",
"relUrl": "/docs/ui-components/typography/"
- },"173": {
+ },"182": {
"doc": "Typography",
"title": "Heading 2",
"content": "Heading 3 . Heading 4 . Heading 5 . Heading 6 . # Heading 1 ## Heading 2 ### Heading 3 #### Heading 4 ##### Heading 5 ###### Heading 6 . ",
"url": "/docs/ui-components/typography/",
"relUrl": "/docs/ui-components/typography/"
- },"174": {
+ },"183": {
"doc": "Typography",
"title": "Body text",
"content": "Default body text is rendered like this: . Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. ",
"url": "/docs/ui-components/typography/#body-text",
"relUrl": "/docs/ui-components/typography/#body-text"
- },"175": {
+ },"184": {
"doc": "Typography",
"title": "Inline elements",
"content": "Text can be bold, italic, or strikethrough. Link to another page. Text can be **bold**, _italic_, or ~~strikethrough~~. [Link to another page](/). ",
"url": "/docs/ui-components/typography/#inline-elements",
"relUrl": "/docs/ui-components/typography/#inline-elements"
- },"176": {
+ },"185": {
"doc": "Typography",
"title": "Typographic Utilities",
"content": "There are a number of specific typographic CSS classes that allow you to override default styling for font size, font weight, line height, and capitalization. View typography utilities . ",
"url": "/docs/ui-components/typography/#typographic-utilities",
"relUrl": "/docs/ui-components/typography/#typographic-utilities"
- },"177": {
+ },"186": {
"doc": "Typography",
"title": "Typography Utilities",
"content": " ",
"url": "/docs/utilities/typography/#typography-utilities",
"relUrl": "/docs/utilities/typography/#typography-utilities"
- },"178": {
+ },"187": {
"doc": "Typography",
"title": "Table of contents",
"content": ". | Font size | Font weight | Line height | Text justification | . ",
"url": "/docs/utilities/typography/#table-of-contents",
"relUrl": "/docs/utilities/typography/#table-of-contents"
- },"179": {
+ },"188": {
"doc": "Typography",
"title": "Font size",
"content": "Use the .fs-1 - .fs-10 to set an explicit font-size. | Class | Small screen size font-size | Large screen size font-size | . | .fs-1 | 9px | 10px | . | .fs-2 | 11px | 12px | . | .fs-3 | 12px | 14px | . | .fs-4 | 14px | 16px | . | .fs-5 | 16px | 18px | . | .fs-6 | 18px | 24px | . | .fs-7 | 24px | 32px | . | .fs-8 | 32px | 38px | . | .fs-9 | 38px | 42px | . | .fs-10 | 42px | 48px | . Font size 1 . Font size 2 . Font size 3 . Font size 4 . Font size 5 . Font size 6 . Font size 7 . Font size 8 . Font size 9 . Font size 10 . In Markdown, use the `{: }` wrapper to apply custom classes: Font size 1 {: .fs-1 } Font size 2 {: .fs-2 } Font size 3 {: .fs-3 } Font size 4 {: .fs-4 } Font size 5 {: .fs-5 } Font size 6 {: .fs-6 } Font size 7 {: .fs-7 } Font size 8 {: .fs-8 } Font size 9 {: .fs-9 } Font size 10 {: .fs-10 } . ",
"url": "/docs/utilities/typography/#font-size",
"relUrl": "/docs/utilities/typography/#font-size"
- },"180": {
+ },"189": {
"doc": "Typography",
"title": "Font weight",
"content": "Use the .fw-300 - .fw-700 to set an explicit font-weight. Font weight 300 . Font weight 400 . Font weight 500 . Font weight 700 . In Markdown, use the `{: }` wrapper to apply custom classes: Font weight 300 {: .fw-300 } Font weight 400 {: .fw-400 } Font weight 500 {: .fw-500 } Font weight 700 {: .fw-700 } . ",
"url": "/docs/utilities/typography/#font-weight",
"relUrl": "/docs/utilities/typography/#font-weight"
- },"181": {
+ },"190": {
"doc": "Typography",
"title": "Line height",
"content": "Use the lh- classes to explicitly apply line height to text. | Class | line-height value | Notes | . | .lh-0 | 0 | | . | .lh-tight | 1.1 | Default for headings | . | .lh-default | 1.4 | Default for body (paragraphs) | . No Line height No Line height . Tight line height Tight line height . Default line height Default line height . In Markdown, use the `{: }` wrapper to apply custom classes: No Line height No Line height {: .lh-0 } Tight line height Tight line height {: .lh-tight } Default line height Default line height {: .fh-default } . ",
"url": "/docs/utilities/typography/#line-height",
"relUrl": "/docs/utilities/typography/#line-height"
- },"182": {
+ },"191": {
"doc": "Typography",
"title": "Text justification",
"content": "By default text is justified left. Use these text- classes to override settings: . | Class | What it does | . | .text-left | text-align: left | . | .text-right | text-align: right | . | .text-center | text-align: center | . ",
"url": "/docs/utilities/typography/#text-justification",
"relUrl": "/docs/utilities/typography/#text-justification"
- },"183": {
+ },"192": {
"doc": "Typography",
"title": "Typography",
"content": " ",
"url": "/docs/utilities/typography/",
"relUrl": "/docs/utilities/typography/"
- },"184": {
+ },"193": {
+ "doc": "Research & Publications",
+ "title": "Coming Soon",
+ "content": " ",
+ "url": "/docs/ui-components#coming-soon",
+
+ "relUrl": "/docs/ui-components#coming-soon"
+ },"194": {
"doc": "Research & Publications",
"title": "Research & Publications",
"content": " ",
"url": "/docs/ui-components",
"relUrl": "/docs/ui-components"
- },"185": {
- "doc": "Mentorship Program",
- "title": "Mentorship Program",
+ },"195": {
+ "doc": "LAI Mentorship Program",
+ "title": "LAI Labs Mentorship Program",
+ "content": "Fostering growth, innovation, and knowledge sharing between experienced AI professionals and aspiring learners. Scroll Down 👇👇 ",
+ "url": "/docs/utilities",
+
+ "relUrl": "/docs/utilities"
+ },"196": {
+ "doc": "LAI Mentorship Program",
+ "title": "Program Details",
+ "content": "The LAI Labs Mentorship Program connects experienced AI professionals with aspiring learners for collaborative project development, research, and skill enhancement. Enrollment Process . | Visit the LAI Labs website and navigate to the Mentorship Program section. | Fill out the application form specifying if you're applying as a mentor or mentee. | Mentees: Describe your background, goals, and areas of interest in AI. | Mentors: Detail your expertise, experience, and mentorship philosophy. | . Benefits . For Mentees: . | Personalized guidance from industry experts | Hands-on experience with real-world AI projects | Networking within the AI community | Skill development in cutting-edge AI technologies | . For Mentors: . | Opportunity to give back to the community | Recognition as a thought leader in AI | Enhancement of leadership and communication skills | . ",
+ "url": "/docs/utilities",
+
+ "relUrl": "/docs/utilities"
+ },"197": {
+ "doc": "LAI Mentorship Program",
+ "title": "Mentor Guidelines",
+ "content": "Ensure that all mentor-mentee interactions adhere to the LAI Labs standards. Communication Channels . Use official platforms like Discord and Google Meet for all interactions. Session Structure . | Weekly one-hour sessions (minimum) | Additional asynchronous communication through Discord | . Responsibilities . | Provide expert guidance in AI concepts and technologies | Assist in project planning and execution | Offer career advice and industry insights | . ",
+ "url": "/docs/utilities",
+
+ "relUrl": "/docs/utilities"
+ },"198": {
+ "doc": "LAI Mentorship Program",
+ "title": "Mentee Guidelines",
+ "content": "Mentees are expected to be committed and proactive during the mentorship period. Program Commitment . | Attend all scheduled sessions with your mentor | Dedicate at least 5 hours per week to program-related work | . Project Requirements . | Develop a project proposal within the first two weeks | Provide weekly progress updates | Present your final project at the end of the program | . ",
+ "url": "/docs/utilities",
+
+ "relUrl": "/docs/utilities"
+ },"199": {
+ "doc": "LAI Mentorship Program",
+ "title": "Register Now",
+ "content": "Mentee Registration . Register as Mentee Mentor Registration . Register as Mentor Have questions? Feel free to reach out to the LAI Labs Mentorship Program Coordinator for more information. We’re here to help you every step of the way! . ",
+ "url": "/docs/utilities",
+
+ "relUrl": "/docs/utilities"
+ },"200": {
+ "doc": "LAI Mentorship Program",
+ "title": "LAI Mentorship Program",
"content": " ",
"url": "/docs/utilities",
diff --git a/_site/docs/AI-Baithak/index.html b/_site/docs/AI-Baithak/index.html
new file mode 100644
index 00000000..2e08242c
--- /dev/null
+++ b/_site/docs/AI-Baithak/index.html
@@ -0,0 +1 @@
+ AI Baithak | Lucknow AISkip to main content
Meet the tech-savvy members of our community! 🚀 These are the masterminds driving innovation with AI, machine learning, and blockchain.
🎯 Rag Rishi
Name:Abhishek Sahu Description: Abhishek is a flutter developer by profession, but his heart truly beats for RAG (Retrieval-Augmented Generation). Wherever he sees documents, the first words out of his mouth are, “Arey, ispe RAG kyun nahi laga rahe ho?” His passion for optimizing retrieval systems and vector databases makes him a true RAG devotee 📚.
But wait, there’s more—Abhishek is also into actual Raag! 🎶 When he’s not diving into neural networks, he’s probably singing classical Indian ragas, proving that his skills extend beyond just tech. Whether it’s a complex query or a classical tune, Rag Rishi will always find the right note! 🎼 More about Rag Rishi
🛠️ Machine Mantri
Name:Prashant Description: Prashant, aka Machine Mantri, runs his own ministry of robots and AI! From making bots play drums 🥁 to ruling the world of Arduino and edge devices, he’s got it all under control.
When he’s not coding a bot’s next move, you’ll find him binge-watching his favorite anime for even more futuristic inspiration 🌟. If there’s a tech problem, Machine Mantri will solve it—probably with a side of robot rock music! 🎸🤖 More about Machine Mantri
🔗 Blockchain Babu
Name:Harsh Joshi Description: Harsh’s mantra is simple: “Centralization ko chhodo, sab kuch blockchain pe lao!” Whether it’s AI, chai, or even your friendships, Harsh believes everything should run on a decentralized ledger 🔐.
From smart contracts to Web3, Blockchain Babu ke hote hue, even your chai breaks might get decentralized! ☕ More about Blockchain Babu
🎤 Speech Shastri
Name:Gauraangi Description: Gauraangi, aka Speech Shastri, doesn’t just hear voices—she makes AI listen to them! A master of turning sound into smarts, she’s the one who cracked the code at Hack2Crack Hackathon, leaving everyone wondering if she secretly trains AI by making it recite Sanskrit shlokas. 📜
From building speech models to fine-tuning them like a classical Raag 🎶, Speech Shastri’s mantra is simple: “If it talks, I’ll make AI understand it!” When she’s not making machines listen, she’s probably convincing them to sing back! 🎵 More about Speech Shastri
🤖 Diffusion Dada
Name:Kaif Description: Kaif is your go-to guy when it comes to anything related to image-based models. You’ve got a blurry image, an artifact problem, or just a random curiosity? Don’t worry, Kaif’s first reaction is always, “Chalo Stable Diffusion lagate hai ispe!” His life revolves around collecting data, fine-tuning models, and optimizing the diffusion process as if it were his morning chai ☕.
Whether it’s upscaling, inpainting, or generating new visuals, Kaif can tackle it all—just don’t be surprised if he starts giving life advice based on latent spaces. When in doubt, let Diffusion Dada sort your pixels out! 🎨 More about Diffusion Dada
🎙️ Join Our Discord
Got any questions related to images, RAG, blockchain, or AI? Feel free to ask our members on Discord!
Content Creation: Help in articles, blogs, educational content on AI/ML.
Workshops/Webinars: Helping in Conducting and facilitating educational sessions.
Mentoring: Guiding Juniors/students in AI/ML.
Opportunities in this category are ideal for those with a knack for teaching and content creation.
Technical and IT Support
IT Management: Support for digital infrastructure and resource management.
GitHub Maintenance: Managing PRs and project upkeep.
Website Management: Updating and ensuring website functionality.
Technical roles
Creative and Multimedia
Graphic Design: Creating visual content for digital platforms and events.
Photography/Videography: Documenting events for promotional use.
These roles are perfect for creatively inclined individuals with skills in design and multimedia.
Community Engagement and Outreach
Community Outreach: Engaging and promoting the mission in various communities.
Social Media: Managing online groups and content dissemination.
Group Administration: Overseeing Discord and WhatsApp groups.
Engagement roles are suited for those with strong communication skills and a passion for community building.
Research and Development
Research Projects: Collaborative innovation and project coordination in AI/ML.
Ideal for individuals interested in cutting-edge AI/ML research and development.
Organizational and Administrative Support
Fundraising: Assisting in fundraising and sponsor relations.
Legal/Compliance: Ensuring legal adherence and managing intellectual property.
Translation/Localization: Making content accessible in multiple languages.
Event Organization: Planning and executing meetups and events.
These roles require organizational skills and attention to detail, ideal for those who excel in administrative tasks.
General Volunteer Application Form
Fill the form given below !
Join the movement to make a difference in the community by volunteering with us. Whether you’re looking to gain new skills, meet like-minded individuals, we have a variety of opportunities available. By filling out our application form, you’ll be taking the first step towards becoming part of a dynamic team dedicated to Accelearte AI Awareness in Lucknow. Our volunteer program is designed to be flexible and accommodating, so whether you have a few hours a week or a few days a month, we have a role that’s right for you. So why wait? Fill out our application form today and start making a difference in the lives of others!”
Content Creation: Help in articles, blogs, educational content on AI/ML.
Workshops/Webinars: Helping in Conducting and facilitating educational sessions.
Mentoring: Guiding Juniors/students in AI/ML.
Opportunities in this category are ideal for those with a knack for teaching and content creation.
Technical and IT Support
IT Management: Support for digital infrastructure and resource management.
GitHub Maintenance: Managing PRs and project upkeep.
Website Management: Updating and ensuring website functionality.
Technical roles
Creative and Multimedia
Graphic Design: Creating visual content for digital platforms and events.
Photography/Videography: Documenting events for promotional use.
These roles are perfect for creatively inclined individuals with skills in design and multimedia.
Community Engagement and Outreach
Community Outreach: Engaging and promoting the mission in various communities.
Social Media: Managing online groups and content dissemination.
Group Administration: Overseeing Discord and WhatsApp groups.
Engagement roles are suited for those with strong communication skills and a passion for community building.
Research and Development
Research Projects: Collaborative innovation and project coordination in AI/ML.
Ideal for individuals interested in cutting-edge AI/ML research and development.
Organizational and Administrative Support
Fundraising: Assisting in fundraising and sponsor relations.
Legal/Compliance: Ensuring legal adherence and managing intellectual property.
Translation/Localization: Making content accessible in multiple languages.
Event Organization: Planning and executing meetups and events.
These roles require organizational skills and attention to detail, ideal for those who excel in administrative tasks.
General Volunteer Application Form
Fill the form given below !
Join the movement to make a difference in the community by volunteering with us. Whether you’re looking to gain new skills, meet like-minded individuals, we have a variety of opportunities available. By filling out our application form, you’ll be taking the first step towards becoming part of a dynamic team dedicated to Accelearte AI Awareness in Lucknow. Our volunteer program is designed to be flexible and accommodating, so whether you have a few hours a week or a few days a month, we have a role that’s right for you. So why wait? Fill out our application form today and start making a difference in the lives of others!”
diff --git a/_site/docs/configuration/index.html b/_site/docs/configuration/index.html
index 560fed4c..8f3c66df 100644
--- a/_site/docs/configuration/index.html
+++ b/_site/docs/configuration/index.html
@@ -1 +1 @@
- About Us | Lucknow AISkip to main content
I wanted to share the story behind why we started this and what drives us. I recently moved to Lucknow and wanted to connect with fellow developers, open-source enthusiasts, and hackers. However, I found that Lucknow lacks such a technology culture and community.
I remember wishing as a college student that I had a mentor to guide me and clarify my doubts. I want the next generation to have those opportunities. So I spoke with friends from Lucknow who now work at various companies and agreed to give back by mentoring youth interested in AI & ML. With that goal, We founded Lucknow AI to advance AI literacy and skills through collaborative workshops, meetups, paper discussions, and community growth.
I am Aaditya (Ankit), a senior research engineer at Saama AI Research Lab with over 6+ years in core AI research. I love hacking things together, building open-source tools, and publishing state-of-the-art research. You can find more about my background & research at aadityaura.github.io
You might be surprised to know that no one in the Lucknow AI community is paid or sponsored. We are just a group of coding geeks and hackers who are passionate about growing the local AI ecosystem!
We nurture Lucknow AI like our own child, volunteering time outside work or college to support the community. Seniors mentor newcomers not due to any obligation but out of a genuine desire to uplift. We contribute open-source code, curate datasets, brainstorm ideas, analyze research papers and more in the quest to push the boundaries of what AI can achieve. And we do it together as one unstoppable, collaborative force!
This is a safe space where you can learn, teach, create, and grow. Imagine the breakthrough innovations we can create when we come together as a supportive, tight-knit community! Let’s put Lucknow on the map in AI and have fun along the way.
If you share this vision, then you have found your tribe. Welcome home!
I wanted to share the story behind why we started this and what drives us. I recently moved to Lucknow and wanted to connect with fellow developers, open-source enthusiasts, and hackers. However, I found that Lucknow lacks such a technology culture and community.
I remember wishing as a college student that I had a mentor to guide me and clarify my doubts. I want the next generation to have those opportunities. So I spoke with friends from Lucknow who now work at various companies and agreed to give back by mentoring youth interested in AI & ML. With that goal, We founded Lucknow AI to advance AI literacy and skills through collaborative workshops, meetups, paper discussions, and community growth.
I am Aaditya (Ankit), a senior research engineer at Saama AI Research Lab with over 6+ years in core AI research. I love hacking things together, building open-source tools, and publishing state-of-the-art research. You can find more about my background & research at aadityaura.github.io
You might be surprised to know that no one in the Lucknow AI community is paid or sponsored. We are just a group of coding geeks and hackers who are passionate about growing the local AI ecosystem!
We nurture Lucknow AI like our own child, volunteering time outside work or college to support the community. Seniors mentor newcomers not due to any obligation but out of a genuine desire to uplift. We contribute open-source code, curate datasets, brainstorm ideas, analyze research papers and more in the quest to push the boundaries of what AI can achieve. And we do it together as one unstoppable, collaborative force!
This is a safe space where you can learn, teach, create, and grow. Imagine the breakthrough innovations we can create when we come together as a supportive, tight-knit community! Let’s put Lucknow on the map in AI and have fun along the way.
If you share this vision, then you have found your tribe. Welcome home!
Excited for the days ahead, ~ Lucknow AI
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- Resources | Lucknow AISkip to main content
To empower the next generation of AI professionals with practical tools, templates, and knowledge to stand out in a competitive job market.
🤝 Contributing
We welcome contributions! Whether you’re sharing your success story, a helpful resource, or improving existing content, your input helps the community grow.
📚 Start Your AI Career Journey
Explore the toolkit, build your skills, and take the next step in your AI career. Your future in AI starts here!
AI-Career-Toolkit is a community-driven project.
Use these resources as inspiration and adapt them to showcase your unique skills and experiences.
2. Learning Resources
An Ultimate Compilation of AI Resources for Mathematics, Machine Learning and Deep Learning
Knowledge Not Shared is wasted. - Clan Jacobs
This collection is a compilation of Excellent ML and DL Tutorials created by the people below
Machine Learning For EveryoneSummarize’s Machine Learning algorithms and their applications in simple words with real-world examples.
Anyone can do Machine Learning
Teachable MachineTrain a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.
Mathematics for Machine LearningIn this post I have compiled great e-resources (MOOC, YouTube Lectures, Books) for learning Mathematics for Machine Learning.
Python NumPy Tutorial for Beginners▶️ Learn the basics of the NumPy library in this tutorial for beginners. It provides background information on how NumPy works and how it compares to Python’s Built-in lists. This video goes through how to write code with NumPy. It starts with the basics of creating arrays and then gets into more advanced stuff. The video covers creating arrays, indexing, math, statistics, reshaping, and more.
DEEP BLUEBERRY BOOKThis is a tiny and very focused collection of links about deep learning. If you’ve always wanted to learn deep learning stuff but don’t know where to start, you might have stumbled upon the right place!
Deep-dive tutorial on Object Detection. Intuition lectures on topics ranging from Classical CV techniques like HOG, SIFT to Convolutional Neural Network based techniques like Overfeat, Faster RCNN etc. You will learn how the ideas have evolved from some of the earliest papers to current ones. And hence the name Evolution of Object Detection Networks.
Visualizing memorization in RNNs by DistillInspecting gradient magnitudes in context can be a powerful tool to see when recurrent units use short-term or long-term contextual understanding.
To empower the next generation of AI professionals with practical tools, templates, and knowledge to stand out in a competitive job market.
🤝 Contributing
We welcome contributions! Whether you’re sharing your success story, a helpful resource, or improving existing content, your input helps the community grow.
📚 Start Your AI Career Journey
Explore the toolkit, build your skills, and take the next step in your AI career. Your future in AI starts here!
AI-Career-Toolkit is a community-driven project.
Use these resources as inspiration and adapt them to showcase your unique skills and experiences.
2. Learning Resources
An Ultimate Compilation of AI Resources for Mathematics, Machine Learning and Deep Learning
Knowledge Not Shared is wasted. - Clan Jacobs
This collection is a compilation of Excellent ML and DL Tutorials created by the people below
Machine Learning For EveryoneSummarize’s Machine Learning algorithms and their applications in simple words with real-world examples.
Anyone can do Machine Learning
Teachable MachineTrain a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.
Mathematics for Machine LearningIn this post I have compiled great e-resources (MOOC, YouTube Lectures, Books) for learning Mathematics for Machine Learning.
Python NumPy Tutorial for Beginners▶️ Learn the basics of the NumPy library in this tutorial for beginners. It provides background information on how NumPy works and how it compares to Python’s Built-in lists. This video goes through how to write code with NumPy. It starts with the basics of creating arrays and then gets into more advanced stuff. The video covers creating arrays, indexing, math, statistics, reshaping, and more.
DEEP BLUEBERRY BOOKThis is a tiny and very focused collection of links about deep learning. If you’ve always wanted to learn deep learning stuff but don’t know where to start, you might have stumbled upon the right place!
Deep-dive tutorial on Object Detection. Intuition lectures on topics ranging from Classical CV techniques like HOG, SIFT to Convolutional Neural Network based techniques like Overfeat, Faster RCNN etc. You will learn how the ideas have evolved from some of the earliest papers to current ones. And hence the name Evolution of Object Detection Networks.
Visualizing memorization in RNNs by DistillInspecting gradient magnitudes in context can be a powerful tool to see when recurrent units use short-term or long-term contextual understanding.
Aaditya and Harsh shared insights into finding and securing internships in today’s competitive landscape. They emphasized the importance of networking, leveraging platforms like LinkedIn, attending industry meetups, and participating in relevant online communities. They advised students to tailor their resumes to highlight skills and projects that align with potential internship roles, and to proactively reach out to companies or professionals in their field of interest.
How to Make a Good GitHub Repo
The speakers discussed best practices for creating a compelling GitHub repository. Key points included:
Organized Structure: Use clear directories and maintain a clean project structure.
Descriptive README: Include a comprehensive README file with project overview, setup instructions, usage examples, and contribution guidelines.
Documentation: Regularly update documentation and ensure code is well-commented.
Version Control: Utilize branches effectively and maintain a consistent commit history.
Company Evaluation: Companies often evaluate candidates by reviewing their GitHub profiles. Therefore, good documentation is crucial as it showcases your skills, project quality, and attention to detail.
Essentials of Proper Documentation and README Files
Effective documentation is crucial for the usability and maintainability of a project. Aaditya and Harsh outlined essential elements of documentation:
README Files: Should provide a summary of the project, installation steps, usage instructions, and contact information.
Code Comments: Write clear comments to explain complex logic or code sections.
Contributing Guidelines: Provide instructions for contributors on how to report issues, submit changes, and follow coding standards.
Ideas for Final Year Projects
The session included brainstorming for innovative final year project ideas. Some suggestions were:
AI-Powered Chatbots: Develop chatbots with advanced conversational abilities for specific domains.
Blockchain-Based Applications: Explore blockchain for secure transactions or decentralized apps.
IoT Solutions: Create IoT-based systems for smart home or environmental monitoring.
Augmented Reality: Build AR applications for educational or entertainment purposes.
Doubt Solving
The AMA also featured a Q&A segment where students and professionals posed their queries. The speakers addressed questions on various topics such as career advice, project development challenges, and industry trends. This interactive segment provided personalized guidance and solutions to specific issues faced by the attendees.
Conclusion
The AMA session with Aaditya and Harsh provided valuable insights into career development, project management, and technical documentation. Attendees gained practical advice on securing internships, creating effective GitHub repositories, and enhancing project documentation, along with exploring innovative ideas for their final year projects. The event was a great opportunity for the community to engage directly with industry leaders and address their career and technical queries.
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- (13/01/24) Jamie AI Voice Assistant Online Meetup | Lucknow AISkip to main content
The Jamie AI Voice Assistant Online Meetup, a collaborative effort between Lucknow AI lab and TFUG Lucknow, highlighted an innovative venture to enhance digital accessibility through AI. This online event, held on January 13, 2024, via Google Meet, assembled a diverse group of technology aficionados, developers, and AI enthusiasts to discuss and explore the potential of voice-assisted technology in making digital interfaces more user-friendly.
Date: January 13, 2024 Time: 2:30 PM Platform: Google Meet
The meetup provided an insightful overview of the Jamie AI Voice Assistant project, emphasizing its mission to simplify the digital experience for users. This initiative represents a significant step towards bridging the gap between complex digital technologies and the everyday user.
Spearheaded by a dynamic team comprising Manso, Mukesh, and Jaswir, the project leverages their collective expertise in JavaScript, Streamlit, and AI development to create a versatile and intuitive voice assistant.
Collaboration between Lucknow AI lab and TFUG Lucknow played a pivotal role in organizing and managing this enriching event, which saw significant participation from individuals across various sectors.
Technical Exploration and Demonstrations
Project Insight
Attendees were introduced to the foundational goals of Jamie AI, designed to act as a tech-savvy companion that offers assistance with a broad spectrum of digital tasks, from mundane to complex.
Technical Infrastructure
A deep dive into the technical underpinnings of Jamie AI, showcasing how Manso’s JavaScript prowess and Mukesh’s Streamlit expertise have contributed to an engaging user interface and responsive front-end experience.
The session highlighted the advanced algorithms employed for image analysis and natural language processing, enabling Jamie AI to understand and execute a wide range of voice commands effectively.
Demonstrations and Applications
Real-time demonstrations of Jamie AI in action provided tangible examples of its potential, illustrating how it can assist users in managing smart home devices and navigating digital platforms, thereby reducing the technological barriers for the less digitally savvy.
Community Engagement and Visionary Future
Engaging the Community
A significant emphasis was placed on community engagement, with participants invited to contribute ideas for improvements, new features, and potential use cases, fostering a collaborative development environment.
Vision for the Future
The Jamie AI team shared their ambitious vision for the voice assistant, discussing plans to expand its functionalities to include navigation assistance, healthcare management, and educational support, among other applications.
Conclusion and Acknowledgements
The Jamie AI Voice Assistant Online Meetup concluded on a high note, with participants and organizers alike excited about the future directions of the project. The event underscored the transformative potential of Jamie AI in making technology accessible to a broader audience and highlighted the critical role of community involvement in driving technological innovation. Special thanks were extended to Manso, Mukesh, and Jaswir for their dedication and contributions, as well as to all participants for their engagement and enthusiasm. This event report captures the spirit and objectives of the Jamie AI Voice Assistant meetup, reflecting on the collaborative effort to democratize access to technology through AI-driven solutions.
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- (21/01/24) Startup Success Days India 2023 | Lucknow AISkip to main content
Startup Success Days India 2023, organized by GDG Lucknow in partnership with TFUG Lucknow, was a pivotal event held at Club Orchid, Lucknow. This event series was crafted to unite Founders, Developers, Mentors, VCs, Industry leaders, Googlers, and enthusiasts to discuss and share insights on the forefront of technological innovation, with a special focus on Generative AI, Google Cloud, Google Maps, Android, Web3, and Language Solutions.
Date and Time: January 21, 10:00 AM – 4:00 PM
Location: Club Orchid, H-306 Faizabad Road, Lucknow, 226028
Key Contributors: GDG Lucknow Team & TFUG Lucknow Team
Inaugural Address: Vasundhara, the GDG Lucknow Organizer, kicked off the event, setting the tone for a day filled with insightful discussions and presentations.
Key Themes: The event revolved around crucial tech and development themes including AI, Career Development, Cloud Computing, Community Building, Enterprise/Business Solutions, Networking, and Women Techmakers.
Objective: The essence of Startup Success Days was to empower startups to leverage Google’s tools and platforms for product development and business growth, while nurturing local ecosystem collaborations.
Session Summaries
Morning Sessions
Discussions began with a deep dive into State Management, exploring its essentials, applications, and best practices.
A Practical Guide to GraphQL provided attendees with actionable insights into implementing GraphQL in their projects.
Thriving on Thin Air session offered strategies for launching businesses with minimal resources, emphasizing efficiency and innovation.
The focus then shifted to the World of IoT using a hybrid cloud approach, highlighting the integration of IoT technologies with cloud computing.
AI/ML in Education sector discussion underscored the transformative potential of artificial intelligence and machine learning in enhancing educational experiences and outcomes.
Afternoon Sessions
A detailed exploration of Pattern Matching in programming languages, discussing its significance and applications.
Panel Discussion: Fostering a New Generation of Developers, facilitated a dialogue among experts on nurturing tech talent and innovation in the developer community.
The discussion on Decentralization of Web Architecture examined the shift towards a more distributed and user-empowered internet structure.
A Session on Adapting Large Language Models (LLMs) to Low Resource Languages: This session, led by Ankit, delved into the challenges and solutions associated with customizing LLMs for languages with limited digital resources. Ankit provided insights into techniques for training models efficiently, ensuring linguistic diversity and accessibility in AI-driven applications. Ankit also participated in the panel discussion, contributing his expertise to broader conversations about developer support and community growth.
A session on Kubernetes covered the essentials of using Kubernetes for managing containerized applications, focusing on its importance in modern software development.
Conclusion
The event concluded with closing remarks, reflected on the day’s learnings and encouraged participants to continue exploring and innovating with the tools and knowledge shared. Startup Success Days India 2023 was not just a conference; it was a beacon for startups and technologists, highlighting the importance of collaboration, continuous learning, and technological advancement. Special thanks were extended to all speakers, for invaluable contributions, and to the organizing teams of GDG and TFUG Lucknow for making this event a resounding success. This daylong journey through various facets of technology and business underscored the vibrant potential of the Lucknow tech community and its role in shaping the future of innovation.
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- 23-24-May-2024-Hack-To-Crack-1.0 | Lucknow AISkip to main content
Hack To Crack 1.0 was an exhilarating 24 hours AI/ML hackathon focused on tackling real-world challenges.
This event has been Orgnised by TFUG Lucknow in collabration with GDG lucknow and Lucknow AI labs.
The event was open to all skill levels, from seasoned data scientists to beginners in AI/ML.
Participants had the opportunity to work in teams, exploring various fields such as computer vision, natural language processing, and reinforcement learning.
Participation and Engagement
33 participants joined the event, forming 9 teams.
The hackathon encouraged collaboration, innovation, and showcasing of talent in AI/ML technologies.
Participants worked on developing intelligent algorithms and implementing predictive models.
Projects and Domains
Automated AI/ML System for Detecting and Mitigating Online Fraud (Online Fraud Detection)
AI-Multilingual-Chatbot (Natural Language Processing)
Batch Audio Transcription Tool (Speech Recognition and Translation)
Bridging the Language Gap: AI-Powered Local Language Transcription and Translation (Natural Language Processing)
Spotify clone (Music Streaming)
Whisper: AI-Powered Local Exploration with RAG-Gemini WhatsApp Bot (Conversational AI)
ChatWithYourPDF (Document Analysis and Conversational AI)
DocGPT (Document Processing and AI)
Winners
First Place: Automated AI/ML System for Detecting and Mitigating Online Fraud Team Name: Veg Kabab, Team: Utkarsh Tiwari
Second Place: Bridging the Language Gap: AI-Powered Local Language Transcription and Translation Team Name: Quaraforce. Team: Aditya Singh, Gaurangi Prakash, Vishal Sarup mathur, Suyash pandey
Third Place: Batch Audio Transcription Tool (Speech Recognition and Translation) Team Name: Pheonix, Team: Anshika Shahi, Divyansh Singh
Impact and Innovation
The event provided a platform for pushing the boundaries of AI innovation.
Participants worked on solutions to empower and assist underserved communities.
The hackathon fostered the development of AI technologies for social good, addressing challenges faced by individuals with disabilities and underserved populations.
Conclusion
Hack To Crack 1.0 successfully brought together AI/ML enthusiasts to collaborate, innovate, and create impactful solutions. The diverse range of projects demonstrated the potential of AI/ML technologies in solving real-world problems and contributing to a more inclusive and equitable society.
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- (25/05/24) Gen AI Awadh Summit | Lucknow AISkip to main content
The Gen AI Awadh Summit, held on May 25, 2024, brought together tech enthusiasts, industry experts, and innovators at the Centre for Advanced Studies, Dr. APJ Abdul Kalam Technical University in Lucknow, India. Organized by TFUG Lucknow and supported by Hunto AI, the summit delved into the latest advancements in artificial intelligence with a special focus on generative AI. The event featured a series of keynotes, workshops, and a hackathon, showcasing AI’s transformative impact across industries.
Date: May 25, 2024 Time: 10:00 AM Venue: 1st Floor, SSB Hall, Dr. APJ Abdul Kalam Technical University, Lucknow, India-226031
Organizers: TFUG Lucknow Sponsors: Hunto AI Collaborations: Google Developer Groups Lucknow
Abhishek discussed fine-tuning Google’s language model Gemma, showcasing practical applications in natural language processing.
Panel Discussion: The Evolution of AI: Past, Present, and Future
A panel of experts engaged in a lively discussion on AI’s growth and future possibilities, with emphasis on its societal and ethical implications.
Hackathon and Community Showcase
The event concluded with a hackathon winner’s felicitation and community project showcase, celebrating innovative AI-driven solutions developed during the summit.
Conclusion
The Gen AI Awadh Summit left attendees inspired and eager to further explore the potential of AI. The event was a testament to the collaborative spirit of the AI community in Lucknow and the broader impact AI can have on society.
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- (26/11/23) Meetup | Lucknow AISkip to main content
Introduction of speakers Ankit, Abhishek, and Neil, bringing many years of experience in data science and AI/ML.
AI/ML Domain Focus
Discussion on Neil’s work in the AI/ML domain, emphasizing the expertise brought to the event.
Lucknow AI Initiative
Insight into the Lucknow AI initiative aimed at fostering an AI-focused community.
ChatGPT and AI Development
Exploration of technologies like ChatGPT and the need for understanding AI development processes.
Plan
Formation of Two Groups: In the following months, we will form two distinct groups - a basic group for beginners and an intermediate group.
Course Selection: The basic group will commence their journey with a Python course, while the intermediate group will dive into a machine learning course.
Weekly Meetups: Post-completion of each course module, we’ll organize weekly meetups. These sessions are designed for doubt clarification and brainstorming, ensuring a thorough understanding of the material.
Educational Video Series: We plan to produce concise, informative videos summarizing each module. These videos will be uploaded to the Lucknow AI YouTube channel.
Benefits of Video Posting:
Enhanced Visibility: Students’ contributions will be showcased, amplifying their learning achievements.
Website Feature: Contributions will be featured on the Lucknow AI website, providing a platform for wider recognition.
Resume Enhancement: Students can include these accomplishments in their resumes, adding significant value.
Social Sharing: Encouraging students to share their learning journey on LinkedIn and other social platforms for broader professional networking.
GitHub Profile Development: Participants are encouraged to create a GitHub profile and consistently upload their module code. - This practice aims to develop a professional and impactful GitHub presence.
Through these initiatives, we aim to foster a robust learning environment, encouraging both skill development and professional growth within the AI community.
AI as a Continuous Journey
Emphasis on AI as a journey of continuous learning and exploration, with a series of milestones.
Community Building and Learning Path
Plans for activities to support beginners in AI, including mentorship and industry interactions.
Addressing the ‘Why AI?’ Question
Discussion on the significance of AI, highlighting recent advancements and impacts of technologies like GPT models.
Practical Application and Internships
The importance of practical experience and internships in AI for societal and national impact.
Networking and Community Support
Stress on networking within the AI community and supporting each other in learning and career development.
Future Engagement Strategies
Plans for future sessions, learning paths, and strategies to maintain active participation.
Participant Interaction
Participants engaged in discussions, sharing their interests and backgrounds.
Concluding Remarks
Encouragement for ongoing learning in AI/ML, stressing its continuous nature.
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The “Build, Train & Deploy” workshop, hosted by TFUG Lucknow and collaborated by LUCKNOW AI LABS, provided a deep dive into the world of AI and ML, ranging from basic neural networks to advanced generative AI models. This event offered a comprehensive educational experience, combining theoretical knowledge with practical coding exercises.
Date: February 27, 2024
The workshop has been featured by the Experience Speakers: Ankit, a Senior AI Research Engineer at Saama and an expert in NLP and AI/ML. and Abhishek Sahu, Senior Software Engineer at BFC Capital P. Ltd, having expertise in the Retrieval-Augmented Generation (RAG), and Flutter.
Held at Shri Ramswaroop College Of Engineering and Management, Lucknow, this workshop attracted over 200 participants, including AI and ML enthusiasts, students, and professionals eager to enhance their understanding and skills in AI technologies.
The workshop featured an in-depth exploration at every stage of learning in AI/ML concepts, facilitated by hands-on sessions with Google Colab, and provided insights into effective project management using GitHub.
Sessions covered ranged from the foundational principles of neural networks to practical implementations of advanced models like BERT and GPT, emphasizing the application of AI in solving real-world problems.
Detailed Sessions Breakdown
Ankit’s Comprehensive AI/ML Overview
Foundational AI Concepts: Ankit began with a strong foundation in neural networks, detailing their design and functionality. This set the stage for understanding more complex AI models.
Advanced AI Models and Techniques: The presentation covered embeddings, attention mechanisms, transformers, and the intricacies of models such as BERT and GPT. Ankit provided practical coding examples, illustrating these concepts’ applications in natural language processing and beyond.
Project Management with GitHub: An essential part of modern AI project development involves using tools like GitHub for collaboration and version control. Ankit’s session offered valuable insights into leveraging GitHub for managing complex AI projects.
Abhishek Sahu’s RAG Model Workshop
Tackling Large Language Models Challenges: Abhishek addressed specific issues inherent in LLMs, such as data hallucination and the need for up-to-date information. Through the lens of the RAG model, he presented solutions that enhance model accuracy and reliability.
Practical Demonstrations: Participants were treated to hands-on demonstrations of RAG implementations, highlighting the model’s ability to improve upon traditional LLMs by incorporating additional data sources for more accurate output.
Audience Engagement and Learning Outcomes
Diverse Participant Group: The workshop was designed to cater to a wide range of participants, from beginners to seasoned professionals. The diverse audience contributed to rich discussions and a dynamic learning environment.
Skill Enhancement and Knowledge Acquisition: Attendees gained valuable skills in AI model development, from basic neural networks to advanced techniques in generative AI, coupled with practical experience in project management using GitHub.
Community Building and Collaboration: The event fostered a sense of community among AI enthusiasts, encouraging ongoing collaboration, exploration, and innovation in the field of AI.
Conclusion
The “Build, Train & Deploy” workshop by LUCKNOW AI LABS and TFUG Lucknow was a transformative event in AI and ML education. It not only provided participants with a thorough understanding of AI technologies but also equipped them with the practical skills necessary for their application in real-world scenarios. The workshop underscored the importance of continuous learning, collaboration, and innovation in the ever-evolving AI landscape, setting a precedent for future educational initiatives in the AI community.
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- (27/01/24) Meetup | Lucknow AISkip to main content
The TensorFlow User Group (TFUG) Lucknow, in collaboration with Lucknow AI Labs, hosted an informative webinar on advanced computer vision techniques, focusing on image processing and the OpenCV library. The event brought together a diverse group of computer vision professionals, researchers, and community groups to foster knowledge sharing and collaboration. AI/ML Domain Focus
The session delved into the intricacies of computer vision, with a specific emphasis on state-of-the-art image processing techniques and the powerful OpenCV library. speaker highlighted the real-world applications of these technologies across various industries, showcasing their potential to revolutionize domains such as autonomous vehicles, medical imaging, and visual analytics. Lucknow AI Initiative
The webinar was part of a larger collaborative effort between TFUG Lucknow and Lucknow AI Labs to promote technology education and drive innovation in the field of artificial intelligence. This initiative aims to empower the local community with cutting-edge knowledge and skills, fostering a thriving ecosystem of AI enthusiasts and professionals.
ChatGPT and AI Development
Discussions also touched upon the advancements in AI-generated visual content, with a focus on the capabilities of models like ChatGPT in generating and processing images. speaker explored the implications of these developments for the field of computer vision and the potential for AI to transform the way we interact with and analyze visual data.
Plan
To support ongoing learning and skill development, the organizers shared plans to provide participants with access to comprehensive learning resources post-event. These resources, including tutorials, documentation, and code samples, will enable attendees to continue advancing their knowledge and expertise in computer vision and OpenCV.
Furthermore, the organizers expressed their intention to explore additional collaborative events focused on specific AI subdomain areas. These targeted sessions will provide deeper insights into niche topics and foster specialized skill development within the community.
AI as a Continuous Journey
The speaker emphasized that image processing and computer vision are rapidly evolving fields, necessitating a continuous learning approach. They stressed the importance of staying updated with the latest advancements, techniques, and tools to remain at the forefront of this dynamic domain.
Community Building and Learning Path
The webinar served as a platform for networking and knowledge exchange among peers and related communities. Attendees had the opportunity to connect with like-minded individuals, share experiences, and explore potential collaborations.
The event provided a solid foundation for members to further their skills in computer vision and OpenCV. The organizers outlined a learning path that included hands-on workshops, project-based learning, and mentorship opportunities to support participants in their journey towards mastery.
Addressing the ‘Why AI?’ Question
The speaker addressed the fundamental question of why AI and computer vision matter in today’s world. They highlighted the diverse real-world applications of image processing and computer vision, ranging from autonomous vehicles and robotics to medical diagnostics and surveillance systems. — By showcasing the tangible impact of these technologies, the event emphasized the significance of investing time and effort in learning and advancing in this field.
Practical Application and Internships
To bridge the gap between theory and practice, the webinar demonstrated applied uses of OpenCV across various industries. speaker shared real-world case studies and examples, illustrating how computer vision techniques are being leveraged to solve complex problems and drive innovation.
The organizers also discussed the importance of internships and practical experience in the field of AI and computer vision. They encouraged participants to seek out opportunities to work on real-world projects and gain hands-on experience, enhancing their employability and industry readiness.
Networking and Community Support
The event facilitated meaningful interactions and networking opportunities among members of TFUG, Lucknow AI Labs, and other related groups. Attendees had the chance to connect with industry experts, researchers, and fellow enthusiasts, fostering a supportive community that encourages knowledge sharing and collaboration.
Future Engagement Strategies
To sustain the momentum and support ongoing learning, the organizers shared plans to provide additional learning resources post-webinar. These resources, including tutorials, documentation, and curated content, will enable participants to deepen their understanding of computer vision and OpenCV.
The organizers also expressed interest in hosting recurring computer vision-focused gatherings, such as workshops, hackathons, and expert talks. These events will provide a platform for continuous skill development, networking, and exposure to the latest trends and technologies in the field.
Participant Interaction
The webinar incorporated an interactive Q&A session, allowing participants to engage with the speaker and seek clarification on various aspects of computer vision and OpenCV. The discussions were lively and insightful, reflecting the enthusiasm and curiosity of the attendees.
Concluding Remarks
The event concluded on a high note, with the speaker emphasizing the immense potential and vibrant future of the Lucknow AI community. They encouraged participants to continue their learning journey, embrace the challenges and opportunities in the field of computer vision, and contribute to the growth of the AI ecosystem in the region.
The organizers expressed their gratitude to the speaker, participants, and collaborators for their support and engagement, reaffirming their commitment to fostering a thriving AI community in Lucknow.
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- (29/06/24) Build with AI 2024 | Lucknow AISkip to main content
The “Build with AI” event series, hosted by Google Developer Groups, was an immersive two-day experience designed to equip developers with the latest AI tools and integration techniques. Held on June 29 and 30, 2024, the event featured a range of sessions from industry experts, hands-on workshops, and interactive discussions. Here’s a detailed overview of the event highlights and key takeaways.
Organizers: Google Developer Groups Collaborations: Various AI and ML Experts
Event Highlights
Day 1 - June 29
LLM INFERENCE using Mediapipe with Gemma
Speaker: Kartikey Rawat (Open Source Manager at CodeLabs | Google Developer Expert in ML) Kartikey delved into using Mediapipe for LLM inference, showcasing its capabilities and applications in AI projects. His session provided insights into leveraging Mediapipe for real-time AI solutions.
AI-Powered Malware: The Evolving Threat Landscape
Speaker: Shrutirupa Banerjee (Senior Security Researcher at Quick Heal Technologies) Shrutirupa discussed the rise of AI-powered malware and the associated security challenges. Her talk highlighted strategies for mitigating threats and enhancing security measures against evolving AI-driven cyber risks.
Localised Intelligence in AI for a Richer AI-UX
Speaker: Harsh Joshi (Founder, DAO Studio) Harsh explored how localized intelligence can improve AI user experiences. He emphasized the importance of tailoring AI solutions to specific regional and cultural contexts to enhance user engagement.
Day 2 - June 30
LLM Powered Application using Advanced RAG Methodology SELF-RAG
Speaker: Jyotishko Biswas (Head of AI for HP Global Treasury) Jyotishko presented on automating contract compliance in Fortune 500 firms using SELF-RAG methodology. His session provided practical insights into applying advanced RAG techniques for efficient document management.
Generative AI Fundamentals
Speaker: Ankit Pal (Senior Research Engineer at Saama | Organizer TFUG Lucknow) Ankit covered the fundamentals of Generative AI, including its principles and applications. His talk was designed to provide a solid foundation for understanding and implementing Generative AI technologies.
Workshop: Intro to RAG with Gemini and Custom Data
Speaker: Abhishek Sahu (Senior Software Engineer at BFC | Co-Organizer GDG, TFUG Lucknow) Abhishek conducted a hands-on workshop on RAG with Gemini, guiding attendees through integrating custom data into RAG workflows. The session was interactive and aimed at practical implementation.
Networking & Swag Distribution
The event featured a networking session, allowing participants to connect with speakers and peers. Google swag was distributed, adding a fun conclusion to the event.
Conclusion
The “Build with AI” series successfully provided valuable knowledge and skills on various aspects of AI. Attendees gained practical experience with AI tools, learned from industry experts, and connected with the developer community, making the event a significant step in advancing their AI journey.
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- (31/08/24) Google I/O Extended Lucknow | Lucknow AISkip to main content
The Google I/O Extended event in Lucknow took place at Integral University on Kursi Road, offering a platform for developers, designers, and tech enthusiasts to gather, learn, and exchange insights on the latest trends in technology. The event was packed with engaging sessions from expert speakers, interactive activities, and plenty of networking opportunities. Here’s a comprehensive overview of the event highlights and key takeaways.
Date: September 10, 2023 Time: 10:00 AM Venue: Integral University, Kursi Road, Dashauli, Uttar Pradesh 226026
Organizers: GDG Lucknow Collaborations: Google Developer Groups India
The event kicked off at 10:00 AM with registration, where attendees were required to present their Entry Pass and a valid photo ID for verification. No on-site registration was available, and participants were reminded to bring their passes in advance.
Key Sessions and Insights
Learning Containers Before You Jump on the Clouds
Speaker: Mritunjay Sharma (Software Engineer at Chainguard) Mritunjay provided a deep dive into the role of containers in modern cloud-native applications. He shared best practices for deploying containers efficiently, emphasizing their benefits for scalability and security.
Beyond the Pixel: The Human Side of Design
Speaker: Vanshita Singh (Co-Organizer at GDG Noida, WTM Ambassador, UI/UX Designer) Vanshita explored the emotional and psychological elements of design, emphasizing the importance of user-centered design principles that go beyond aesthetics. Her talk highlighted how understanding user behavior can lead to more effective design solutions.
Quiz Session
A fun and interactive quiz session was conducted to test participants’ knowledge on tech topics covered during the event. This engaging activity offered a lively break for all attendees.
Integrating Gemini AI with Jetpack Compose
Speaker: Akash Verma Akash introduced the audience to Gemini AI and demonstrated how to integrate it with Jetpack Compose, Google’s modern UI toolkit for Android. He showed how developers can leverage AI to create more responsive and intelligent Android apps.
Build a Seamless and Intuitive Product with Jakob Nielsen’s Heuristic Principles
Speaker: Aryendra Prakash Singh (Co-Organizer at GDG Noida, Design Lead at Publicis Sapient) Aryendra presented Jakob Nielsen’s 10 Usability Heuristics, providing practical advice on applying these principles to create intuitive and user-friendly products.
Introduction to Project IDX and Firebase Genkit | Build an Agent-Powered App with Generative AI
Attendees were introduced to Google’s latest tools, Project IDX and Firebase Genkit, which facilitate the development of AI-powered applications. This session showcased how to build apps that integrate Generative AI, offering new ways to enhance app functionality.
Networking & Swag Distribution
The event concluded with a networking session, where participants had the opportunity to engage with speakers and fellow developers. Google swag was distributed, adding a fun and memorable touch to the end of the day.
Conclusion
Google I/O Extended Lucknow 2023 was a highly informative and engaging event. Attendees gained valuable insights into containers, AI integration, product design, and usability, all while building stronger connections within the local developer community.
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- AI Baithak | Lucknow AISkip to main content
Meet the tech-savvy members of our community! 🚀 These are the masterminds driving innovation with AI, machine learning, and blockchain.
🎯 Rag Rishi
Name:Abhishek Sahu Description: Abhishek is a flutter developer by profession, but his heart truly beats for RAG (Retrieval-Augmented Generation). Wherever he sees documents, the first words out of his mouth are, “Arey, ispe RAG kyun nahi laga rahe ho?” His passion for optimizing retrieval systems and vector databases makes him a true RAG devotee 📚.
But wait, there’s more—Abhishek is also into actual Raag! 🎶 When he’s not diving into neural networks, he’s probably singing classical Indian ragas, proving that his skills extend beyond just tech. Whether it’s a complex query or a classical tune, Rag Rishi will always find the right note! 🎼 More about Rag Rishi
🛠️ Machine Mantri
Name:Prashant Description: Prashant, aka Machine Mantri, runs his own ministry of robots and AI! From making bots play drums 🥁 to ruling the world of Arduino and edge devices, he’s got it all under control.
When he’s not coding a bot’s next move, you’ll find him binge-watching his favorite anime for even more futuristic inspiration 🌟. If there’s a tech problem, Machine Mantri will solve it—probably with a side of robot rock music! 🎸🤖 More about Machine Mantri
🔗 Blockchain Babu
Name:Harsh Joshi Description: Harsh’s mantra is simple: “Centralization ko chhodo, sab kuch blockchain pe lao!” Whether it’s AI, chai, or even your friendships, Harsh believes everything should run on a decentralized ledger 🔐.
From smart contracts to Web3, Blockchain Babu ke hote hue, even your chai breaks might get decentralized! ☕ More about Blockchain Babu
🎤 Speech Shastri
Name:Gauraangi Description: Gauraangi, aka Speech Shastri, doesn’t just hear voices—she makes AI listen to them! A master of turning sound into smarts, she’s the one who cracked the code at Hack2Crack Hackathon, leaving everyone wondering if she secretly trains AI by making it recite Sanskrit shlokas. 📜
From building speech models to fine-tuning them like a classical Raag 🎶, Speech Shastri’s mantra is simple: “If it talks, I’ll make AI understand it!” When she’s not making machines listen, she’s probably convincing them to sing back! 🎵 More about Speech Shastri
🤖 Diffusion Dada
Name:Kaif Description: Kaif is your go-to guy when it comes to anything related to image-based models. You’ve got a blurry image, an artifact problem, or just a random curiosity? Don’t worry, Kaif’s first reaction is always, “Chalo Stable Diffusion lagate hai ispe!” His life revolves around collecting data, fine-tuning models, and optimizing the diffusion process as if it were his morning chai ☕.
Whether it’s upscaling, inpainting, or generating new visuals, Kaif can tackle it all—just don’t be surprised if he starts giving life advice based on latent spaces. When in doubt, let Diffusion Dada sort your pixels out! 🎨 More about Diffusion Dada
🎙️ Join Our Discord
Got any questions related to images, RAG, blockchain, or AI? Feel free to ask our members on Discord!
Aaditya and Harsh shared insights into finding and securing internships in today’s competitive landscape. They emphasized the importance of networking, leveraging platforms like LinkedIn, attending industry meetups, and participating in relevant online communities. They advised students to tailor their resumes to highlight skills and projects that align with potential internship roles, and to proactively reach out to companies or professionals in their field of interest.
How to Make a Good GitHub Repo
The speakers discussed best practices for creating a compelling GitHub repository. Key points included:
Organized Structure: Use clear directories and maintain a clean project structure.
Descriptive README: Include a comprehensive README file with project overview, setup instructions, usage examples, and contribution guidelines.
Documentation: Regularly update documentation and ensure code is well-commented.
Version Control: Utilize branches effectively and maintain a consistent commit history.
Company Evaluation: Companies often evaluate candidates by reviewing their GitHub profiles. Therefore, good documentation is crucial as it showcases your skills, project quality, and attention to detail.
Essentials of Proper Documentation and README Files
Effective documentation is crucial for the usability and maintainability of a project. Aaditya and Harsh outlined essential elements of documentation:
README Files: Should provide a summary of the project, installation steps, usage instructions, and contact information.
Code Comments: Write clear comments to explain complex logic or code sections.
Contributing Guidelines: Provide instructions for contributors on how to report issues, submit changes, and follow coding standards.
Ideas for Final Year Projects
The session included brainstorming for innovative final year project ideas. Some suggestions were:
AI-Powered Chatbots: Develop chatbots with advanced conversational abilities for specific domains.
Blockchain-Based Applications: Explore blockchain for secure transactions or decentralized apps.
IoT Solutions: Create IoT-based systems for smart home or environmental monitoring.
Augmented Reality: Build AR applications for educational or entertainment purposes.
Doubt Solving
The AMA also featured a Q&A segment where students and professionals posed their queries. The speakers addressed questions on various topics such as career advice, project development challenges, and industry trends. This interactive segment provided personalized guidance and solutions to specific issues faced by the attendees.
Conclusion
The AMA session with Aaditya and Harsh provided valuable insights into career development, project management, and technical documentation. Attendees gained practical advice on securing internships, creating effective GitHub repositories, and enhancing project documentation, along with exploring innovative ideas for their final year projects. The event was a great opportunity for the community to engage directly with industry leaders and address their career and technical queries.
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+ (13/01/24) Jamie AI Voice Assistant Online Meetup | Lucknow AISkip to main content
The Jamie AI Voice Assistant Online Meetup, a collaborative effort between Lucknow AI lab and TFUG Lucknow, highlighted an innovative venture to enhance digital accessibility through AI. This online event, held on January 13, 2024, via Google Meet, assembled a diverse group of technology aficionados, developers, and AI enthusiasts to discuss and explore the potential of voice-assisted technology in making digital interfaces more user-friendly.
Date: January 13, 2024 Time: 2:30 PM Platform: Google Meet
The meetup provided an insightful overview of the Jamie AI Voice Assistant project, emphasizing its mission to simplify the digital experience for users. This initiative represents a significant step towards bridging the gap between complex digital technologies and the everyday user.
Spearheaded by a dynamic team comprising Manso, Mukesh, and Jaswir, the project leverages their collective expertise in JavaScript, Streamlit, and AI development to create a versatile and intuitive voice assistant.
Collaboration between Lucknow AI lab and TFUG Lucknow played a pivotal role in organizing and managing this enriching event, which saw significant participation from individuals across various sectors.
Technical Exploration and Demonstrations
Project Insight
Attendees were introduced to the foundational goals of Jamie AI, designed to act as a tech-savvy companion that offers assistance with a broad spectrum of digital tasks, from mundane to complex.
Technical Infrastructure
A deep dive into the technical underpinnings of Jamie AI, showcasing how Manso’s JavaScript prowess and Mukesh’s Streamlit expertise have contributed to an engaging user interface and responsive front-end experience.
The session highlighted the advanced algorithms employed for image analysis and natural language processing, enabling Jamie AI to understand and execute a wide range of voice commands effectively.
Demonstrations and Applications
Real-time demonstrations of Jamie AI in action provided tangible examples of its potential, illustrating how it can assist users in managing smart home devices and navigating digital platforms, thereby reducing the technological barriers for the less digitally savvy.
Community Engagement and Visionary Future
Engaging the Community
A significant emphasis was placed on community engagement, with participants invited to contribute ideas for improvements, new features, and potential use cases, fostering a collaborative development environment.
Vision for the Future
The Jamie AI team shared their ambitious vision for the voice assistant, discussing plans to expand its functionalities to include navigation assistance, healthcare management, and educational support, among other applications.
Conclusion and Acknowledgements
The Jamie AI Voice Assistant Online Meetup concluded on a high note, with participants and organizers alike excited about the future directions of the project. The event underscored the transformative potential of Jamie AI in making technology accessible to a broader audience and highlighted the critical role of community involvement in driving technological innovation. Special thanks were extended to Manso, Mukesh, and Jaswir for their dedication and contributions, as well as to all participants for their engagement and enthusiasm. This event report captures the spirit and objectives of the Jamie AI Voice Assistant meetup, reflecting on the collaborative effort to democratize access to technology through AI-driven solutions.
diff --git a/_site/docs/layout/Events & Meetups/21-Jan-24-Startup_Success_days_GdgLko/index.html b/_site/docs/layout/Events & Meetups/21-Jan-24-Startup_Success_days_GdgLko/index.html
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+ (21/01/24) Startup Success Days India 2023 | Lucknow AISkip to main content
Startup Success Days India 2023, organized by GDG Lucknow in partnership with TFUG Lucknow, was a pivotal event held at Club Orchid, Lucknow. This event series was crafted to unite Founders, Developers, Mentors, VCs, Industry leaders, Googlers, and enthusiasts to discuss and share insights on the forefront of technological innovation, with a special focus on Generative AI, Google Cloud, Google Maps, Android, Web3, and Language Solutions.
Date and Time: January 21, 10:00 AM – 4:00 PM
Location: Club Orchid, H-306 Faizabad Road, Lucknow, 226028
Key Contributors: GDG Lucknow Team & TFUG Lucknow Team
Inaugural Address: Vasundhara, the GDG Lucknow Organizer, kicked off the event, setting the tone for a day filled with insightful discussions and presentations.
Key Themes: The event revolved around crucial tech and development themes including AI, Career Development, Cloud Computing, Community Building, Enterprise/Business Solutions, Networking, and Women Techmakers.
Objective: The essence of Startup Success Days was to empower startups to leverage Google’s tools and platforms for product development and business growth, while nurturing local ecosystem collaborations.
Session Summaries
Morning Sessions
Discussions began with a deep dive into State Management, exploring its essentials, applications, and best practices.
A Practical Guide to GraphQL provided attendees with actionable insights into implementing GraphQL in their projects.
Thriving on Thin Air session offered strategies for launching businesses with minimal resources, emphasizing efficiency and innovation.
The focus then shifted to the World of IoT using a hybrid cloud approach, highlighting the integration of IoT technologies with cloud computing.
AI/ML in Education sector discussion underscored the transformative potential of artificial intelligence and machine learning in enhancing educational experiences and outcomes.
Afternoon Sessions
A detailed exploration of Pattern Matching in programming languages, discussing its significance and applications.
Panel Discussion: Fostering a New Generation of Developers, facilitated a dialogue among experts on nurturing tech talent and innovation in the developer community.
The discussion on Decentralization of Web Architecture examined the shift towards a more distributed and user-empowered internet structure.
A Session on Adapting Large Language Models (LLMs) to Low Resource Languages: This session, led by Ankit, delved into the challenges and solutions associated with customizing LLMs for languages with limited digital resources. Ankit provided insights into techniques for training models efficiently, ensuring linguistic diversity and accessibility in AI-driven applications. Ankit also participated in the panel discussion, contributing his expertise to broader conversations about developer support and community growth.
A session on Kubernetes covered the essentials of using Kubernetes for managing containerized applications, focusing on its importance in modern software development.
Conclusion
The event concluded with closing remarks, reflected on the day’s learnings and encouraged participants to continue exploring and innovating with the tools and knowledge shared. Startup Success Days India 2023 was not just a conference; it was a beacon for startups and technologists, highlighting the importance of collaboration, continuous learning, and technological advancement. Special thanks were extended to all speakers, for invaluable contributions, and to the organizing teams of GDG and TFUG Lucknow for making this event a resounding success. This daylong journey through various facets of technology and business underscored the vibrant potential of the Lucknow tech community and its role in shaping the future of innovation.
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+ 23-24-May-2024-Hack-To-Crack-1.0 | Lucknow AISkip to main content
Hack To Crack 1.0 was an exhilarating 24 hours AI/ML hackathon focused on tackling real-world challenges.
This event has been Orgnised by TFUG Lucknow in collabration with GDG lucknow and Lucknow AI labs.
The event was open to all skill levels, from seasoned data scientists to beginners in AI/ML.
Participants had the opportunity to work in teams, exploring various fields such as computer vision, natural language processing, and reinforcement learning.
Participation and Engagement
33 participants joined the event, forming 9 teams.
The hackathon encouraged collaboration, innovation, and showcasing of talent in AI/ML technologies.
Participants worked on developing intelligent algorithms and implementing predictive models.
Projects and Domains
Automated AI/ML System for Detecting and Mitigating Online Fraud (Online Fraud Detection)
AI-Multilingual-Chatbot (Natural Language Processing)
Batch Audio Transcription Tool (Speech Recognition and Translation)
Bridging the Language Gap: AI-Powered Local Language Transcription and Translation (Natural Language Processing)
Spotify clone (Music Streaming)
Whisper: AI-Powered Local Exploration with RAG-Gemini WhatsApp Bot (Conversational AI)
ChatWithYourPDF (Document Analysis and Conversational AI)
DocGPT (Document Processing and AI)
Winners
First Place: Automated AI/ML System for Detecting and Mitigating Online Fraud Team Name: Veg Kabab, Team: Utkarsh Tiwari
Second Place: Bridging the Language Gap: AI-Powered Local Language Transcription and Translation Team Name: Quaraforce. Team: Aditya Singh, Gaurangi Prakash, Vishal Sarup mathur, Suyash pandey
Third Place: Batch Audio Transcription Tool (Speech Recognition and Translation) Team Name: Pheonix, Team: Anshika Shahi, Divyansh Singh
Impact and Innovation
The event provided a platform for pushing the boundaries of AI innovation.
Participants worked on solutions to empower and assist underserved communities.
The hackathon fostered the development of AI technologies for social good, addressing challenges faced by individuals with disabilities and underserved populations.
Conclusion
Hack To Crack 1.0 successfully brought together AI/ML enthusiasts to collaborate, innovate, and create impactful solutions. The diverse range of projects demonstrated the potential of AI/ML technologies in solving real-world problems and contributing to a more inclusive and equitable society.
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The Gen AI Awadh Summit, held on May 25, 2024, brought together tech enthusiasts, industry experts, and innovators at the Centre for Advanced Studies, Dr. APJ Abdul Kalam Technical University in Lucknow, India. Organized by TFUG Lucknow and supported by Hunto AI, the summit delved into the latest advancements in artificial intelligence with a special focus on generative AI. The event featured a series of keynotes, workshops, and a hackathon, showcasing AI’s transformative impact across industries.
Date: May 25, 2024 Time: 10:00 AM Venue: 1st Floor, SSB Hall, Dr. APJ Abdul Kalam Technical University, Lucknow, India-226031
Organizers: TFUG Lucknow Sponsors: Hunto AI Collaborations: Google Developer Groups Lucknow
Abhishek discussed fine-tuning Google’s language model Gemma, showcasing practical applications in natural language processing.
Panel Discussion: The Evolution of AI: Past, Present, and Future
A panel of experts engaged in a lively discussion on AI’s growth and future possibilities, with emphasis on its societal and ethical implications.
Hackathon and Community Showcase
The event concluded with a hackathon winner’s felicitation and community project showcase, celebrating innovative AI-driven solutions developed during the summit.
Conclusion
The Gen AI Awadh Summit left attendees inspired and eager to further explore the potential of AI. The event was a testament to the collaborative spirit of the AI community in Lucknow and the broader impact AI can have on society.
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Introduction of speakers Ankit, Abhishek, and Neil, bringing many years of experience in data science and AI/ML.
AI/ML Domain Focus
Discussion on Neil’s work in the AI/ML domain, emphasizing the expertise brought to the event.
Lucknow AI Initiative
Insight into the Lucknow AI initiative aimed at fostering an AI-focused community.
ChatGPT and AI Development
Exploration of technologies like ChatGPT and the need for understanding AI development processes.
Plan
Formation of Two Groups: In the following months, we will form two distinct groups - a basic group for beginners and an intermediate group.
Course Selection: The basic group will commence their journey with a Python course, while the intermediate group will dive into a machine learning course.
Weekly Meetups: Post-completion of each course module, we’ll organize weekly meetups. These sessions are designed for doubt clarification and brainstorming, ensuring a thorough understanding of the material.
Educational Video Series: We plan to produce concise, informative videos summarizing each module. These videos will be uploaded to the Lucknow AI YouTube channel.
Benefits of Video Posting:
Enhanced Visibility: Students’ contributions will be showcased, amplifying their learning achievements.
Website Feature: Contributions will be featured on the Lucknow AI website, providing a platform for wider recognition.
Resume Enhancement: Students can include these accomplishments in their resumes, adding significant value.
Social Sharing: Encouraging students to share their learning journey on LinkedIn and other social platforms for broader professional networking.
GitHub Profile Development: Participants are encouraged to create a GitHub profile and consistently upload their module code. - This practice aims to develop a professional and impactful GitHub presence.
Through these initiatives, we aim to foster a robust learning environment, encouraging both skill development and professional growth within the AI community.
AI as a Continuous Journey
Emphasis on AI as a journey of continuous learning and exploration, with a series of milestones.
Community Building and Learning Path
Plans for activities to support beginners in AI, including mentorship and industry interactions.
Addressing the ‘Why AI?’ Question
Discussion on the significance of AI, highlighting recent advancements and impacts of technologies like GPT models.
Practical Application and Internships
The importance of practical experience and internships in AI for societal and national impact.
Networking and Community Support
Stress on networking within the AI community and supporting each other in learning and career development.
Future Engagement Strategies
Plans for future sessions, learning paths, and strategies to maintain active participation.
Participant Interaction
Participants engaged in discussions, sharing their interests and backgrounds.
Concluding Remarks
Encouragement for ongoing learning in AI/ML, stressing its continuous nature.
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+ (27/02/24) Build, Train & Deploy Workshop | Lucknow AISkip to main content
The “Build, Train & Deploy” workshop, hosted by TFUG Lucknow and collaborated by LUCKNOW AI LABS, provided a deep dive into the world of AI and ML, ranging from basic neural networks to advanced generative AI models. This event offered a comprehensive educational experience, combining theoretical knowledge with practical coding exercises.
Date: February 27, 2024
The workshop has been featured by the Experience Speakers: Ankit, a Senior AI Research Engineer at Saama and an expert in NLP and AI/ML. and Abhishek Sahu, Senior Software Engineer at BFC Capital P. Ltd, having expertise in the Retrieval-Augmented Generation (RAG), and Flutter.
Held at Shri Ramswaroop College Of Engineering and Management, Lucknow, this workshop attracted over 200 participants, including AI and ML enthusiasts, students, and professionals eager to enhance their understanding and skills in AI technologies.
The workshop featured an in-depth exploration at every stage of learning in AI/ML concepts, facilitated by hands-on sessions with Google Colab, and provided insights into effective project management using GitHub.
Sessions covered ranged from the foundational principles of neural networks to practical implementations of advanced models like BERT and GPT, emphasizing the application of AI in solving real-world problems.
Detailed Sessions Breakdown
Ankit’s Comprehensive AI/ML Overview
Foundational AI Concepts: Ankit began with a strong foundation in neural networks, detailing their design and functionality. This set the stage for understanding more complex AI models.
Advanced AI Models and Techniques: The presentation covered embeddings, attention mechanisms, transformers, and the intricacies of models such as BERT and GPT. Ankit provided practical coding examples, illustrating these concepts’ applications in natural language processing and beyond.
Project Management with GitHub: An essential part of modern AI project development involves using tools like GitHub for collaboration and version control. Ankit’s session offered valuable insights into leveraging GitHub for managing complex AI projects.
Abhishek Sahu’s RAG Model Workshop
Tackling Large Language Models Challenges: Abhishek addressed specific issues inherent in LLMs, such as data hallucination and the need for up-to-date information. Through the lens of the RAG model, he presented solutions that enhance model accuracy and reliability.
Practical Demonstrations: Participants were treated to hands-on demonstrations of RAG implementations, highlighting the model’s ability to improve upon traditional LLMs by incorporating additional data sources for more accurate output.
Audience Engagement and Learning Outcomes
Diverse Participant Group: The workshop was designed to cater to a wide range of participants, from beginners to seasoned professionals. The diverse audience contributed to rich discussions and a dynamic learning environment.
Skill Enhancement and Knowledge Acquisition: Attendees gained valuable skills in AI model development, from basic neural networks to advanced techniques in generative AI, coupled with practical experience in project management using GitHub.
Community Building and Collaboration: The event fostered a sense of community among AI enthusiasts, encouraging ongoing collaboration, exploration, and innovation in the field of AI.
Conclusion
The “Build, Train & Deploy” workshop by LUCKNOW AI LABS and TFUG Lucknow was a transformative event in AI and ML education. It not only provided participants with a thorough understanding of AI technologies but also equipped them with the practical skills necessary for their application in real-world scenarios. The workshop underscored the importance of continuous learning, collaboration, and innovation in the ever-evolving AI landscape, setting a precedent for future educational initiatives in the AI community.
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+ (27/01/24) Meetup | Lucknow AISkip to main content
The TensorFlow User Group (TFUG) Lucknow, in collaboration with Lucknow AI Labs, hosted an informative webinar on advanced computer vision techniques, focusing on image processing and the OpenCV library. The event brought together a diverse group of computer vision professionals, researchers, and community groups to foster knowledge sharing and collaboration. AI/ML Domain Focus
The session delved into the intricacies of computer vision, with a specific emphasis on state-of-the-art image processing techniques and the powerful OpenCV library. speaker highlighted the real-world applications of these technologies across various industries, showcasing their potential to revolutionize domains such as autonomous vehicles, medical imaging, and visual analytics. Lucknow AI Initiative
The webinar was part of a larger collaborative effort between TFUG Lucknow and Lucknow AI Labs to promote technology education and drive innovation in the field of artificial intelligence. This initiative aims to empower the local community with cutting-edge knowledge and skills, fostering a thriving ecosystem of AI enthusiasts and professionals.
ChatGPT and AI Development
Discussions also touched upon the advancements in AI-generated visual content, with a focus on the capabilities of models like ChatGPT in generating and processing images. speaker explored the implications of these developments for the field of computer vision and the potential for AI to transform the way we interact with and analyze visual data.
Plan
To support ongoing learning and skill development, the organizers shared plans to provide participants with access to comprehensive learning resources post-event. These resources, including tutorials, documentation, and code samples, will enable attendees to continue advancing their knowledge and expertise in computer vision and OpenCV.
Furthermore, the organizers expressed their intention to explore additional collaborative events focused on specific AI subdomain areas. These targeted sessions will provide deeper insights into niche topics and foster specialized skill development within the community.
AI as a Continuous Journey
The speaker emphasized that image processing and computer vision are rapidly evolving fields, necessitating a continuous learning approach. They stressed the importance of staying updated with the latest advancements, techniques, and tools to remain at the forefront of this dynamic domain.
Community Building and Learning Path
The webinar served as a platform for networking and knowledge exchange among peers and related communities. Attendees had the opportunity to connect with like-minded individuals, share experiences, and explore potential collaborations.
The event provided a solid foundation for members to further their skills in computer vision and OpenCV. The organizers outlined a learning path that included hands-on workshops, project-based learning, and mentorship opportunities to support participants in their journey towards mastery.
Addressing the ‘Why AI?’ Question
The speaker addressed the fundamental question of why AI and computer vision matter in today’s world. They highlighted the diverse real-world applications of image processing and computer vision, ranging from autonomous vehicles and robotics to medical diagnostics and surveillance systems. — By showcasing the tangible impact of these technologies, the event emphasized the significance of investing time and effort in learning and advancing in this field.
Practical Application and Internships
To bridge the gap between theory and practice, the webinar demonstrated applied uses of OpenCV across various industries. speaker shared real-world case studies and examples, illustrating how computer vision techniques are being leveraged to solve complex problems and drive innovation.
The organizers also discussed the importance of internships and practical experience in the field of AI and computer vision. They encouraged participants to seek out opportunities to work on real-world projects and gain hands-on experience, enhancing their employability and industry readiness.
Networking and Community Support
The event facilitated meaningful interactions and networking opportunities among members of TFUG, Lucknow AI Labs, and other related groups. Attendees had the chance to connect with industry experts, researchers, and fellow enthusiasts, fostering a supportive community that encourages knowledge sharing and collaboration.
Future Engagement Strategies
To sustain the momentum and support ongoing learning, the organizers shared plans to provide additional learning resources post-webinar. These resources, including tutorials, documentation, and curated content, will enable participants to deepen their understanding of computer vision and OpenCV.
The organizers also expressed interest in hosting recurring computer vision-focused gatherings, such as workshops, hackathons, and expert talks. These events will provide a platform for continuous skill development, networking, and exposure to the latest trends and technologies in the field.
Participant Interaction
The webinar incorporated an interactive Q&A session, allowing participants to engage with the speaker and seek clarification on various aspects of computer vision and OpenCV. The discussions were lively and insightful, reflecting the enthusiasm and curiosity of the attendees.
Concluding Remarks
The event concluded on a high note, with the speaker emphasizing the immense potential and vibrant future of the Lucknow AI community. They encouraged participants to continue their learning journey, embrace the challenges and opportunities in the field of computer vision, and contribute to the growth of the AI ecosystem in the region.
The organizers expressed their gratitude to the speaker, participants, and collaborators for their support and engagement, reaffirming their commitment to fostering a thriving AI community in Lucknow.
diff --git a/_site/docs/layout/Events & Meetups/29-Jun-2024 Build with AI/index.html b/_site/docs/layout/Events & Meetups/29-Jun-2024 Build with AI/index.html
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The “Build with AI” event series, hosted by Google Developer Groups, was an immersive two-day experience designed to equip developers with the latest AI tools and integration techniques. Held on June 29 and 30, 2024, the event featured a range of sessions from industry experts, hands-on workshops, and interactive discussions. Here’s a detailed overview of the event highlights and key takeaways.
Organizers: Google Developer Groups Collaborations: Various AI and ML Experts
Event Highlights
Day 1 - June 29
LLM INFERENCE using Mediapipe with Gemma
Speaker: Kartikey Rawat (Open Source Manager at CodeLabs | Google Developer Expert in ML) Kartikey delved into using Mediapipe for LLM inference, showcasing its capabilities and applications in AI projects. His session provided insights into leveraging Mediapipe for real-time AI solutions.
AI-Powered Malware: The Evolving Threat Landscape
Speaker: Shrutirupa Banerjee (Senior Security Researcher at Quick Heal Technologies) Shrutirupa discussed the rise of AI-powered malware and the associated security challenges. Her talk highlighted strategies for mitigating threats and enhancing security measures against evolving AI-driven cyber risks.
Localised Intelligence in AI for a Richer AI-UX
Speaker: Harsh Joshi (Founder, DAO Studio) Harsh explored how localized intelligence can improve AI user experiences. He emphasized the importance of tailoring AI solutions to specific regional and cultural contexts to enhance user engagement.
Day 2 - June 30
LLM Powered Application using Advanced RAG Methodology SELF-RAG
Speaker: Jyotishko Biswas (Head of AI for HP Global Treasury) Jyotishko presented on automating contract compliance in Fortune 500 firms using SELF-RAG methodology. His session provided practical insights into applying advanced RAG techniques for efficient document management.
Generative AI Fundamentals
Speaker: Ankit Pal (Senior Research Engineer at Saama | Organizer TFUG Lucknow) Ankit covered the fundamentals of Generative AI, including its principles and applications. His talk was designed to provide a solid foundation for understanding and implementing Generative AI technologies.
Workshop: Intro to RAG with Gemini and Custom Data
Speaker: Abhishek Sahu (Senior Software Engineer at BFC | Co-Organizer GDG, TFUG Lucknow) Abhishek conducted a hands-on workshop on RAG with Gemini, guiding attendees through integrating custom data into RAG workflows. The session was interactive and aimed at practical implementation.
Networking & Swag Distribution
The event featured a networking session, allowing participants to connect with speakers and peers. Google swag was distributed, adding a fun conclusion to the event.
Conclusion
The “Build with AI” series successfully provided valuable knowledge and skills on various aspects of AI. Attendees gained practical experience with AI tools, learned from industry experts, and connected with the developer community, making the event a significant step in advancing their AI journey.
diff --git a/_site/docs/layout/Events & Meetups/31-Aug-2024 Google IO Extend/index.html b/_site/docs/layout/Events & Meetups/31-Aug-2024 Google IO Extend/index.html
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+ (31/08/24) Google I/O Extended Lucknow | Lucknow AISkip to main content
The Google I/O Extended event in Lucknow took place at Integral University on Kursi Road, offering a platform for developers, designers, and tech enthusiasts to gather, learn, and exchange insights on the latest trends in technology. The event was packed with engaging sessions from expert speakers, interactive activities, and plenty of networking opportunities. Here’s a comprehensive overview of the event highlights and key takeaways.
Date: September 10, 2023 Time: 10:00 AM Venue: Integral University, Kursi Road, Dashauli, Uttar Pradesh 226026
Organizers: GDG Lucknow Collaborations: Google Developer Groups India
The event kicked off at 10:00 AM with registration, where attendees were required to present their Entry Pass and a valid photo ID for verification. No on-site registration was available, and participants were reminded to bring their passes in advance.
Key Sessions and Insights
Learning Containers Before You Jump on the Clouds
Speaker: Mritunjay Sharma (Software Engineer at Chainguard) Mritunjay provided a deep dive into the role of containers in modern cloud-native applications. He shared best practices for deploying containers efficiently, emphasizing their benefits for scalability and security.
Beyond the Pixel: The Human Side of Design
Speaker: Vanshita Singh (Co-Organizer at GDG Noida, WTM Ambassador, UI/UX Designer) Vanshita explored the emotional and psychological elements of design, emphasizing the importance of user-centered design principles that go beyond aesthetics. Her talk highlighted how understanding user behavior can lead to more effective design solutions.
Quiz Session
A fun and interactive quiz session was conducted to test participants’ knowledge on tech topics covered during the event. This engaging activity offered a lively break for all attendees.
Integrating Gemini AI with Jetpack Compose
Speaker: Akash Verma Akash introduced the audience to Gemini AI and demonstrated how to integrate it with Jetpack Compose, Google’s modern UI toolkit for Android. He showed how developers can leverage AI to create more responsive and intelligent Android apps.
Build a Seamless and Intuitive Product with Jakob Nielsen’s Heuristic Principles
Speaker: Aryendra Prakash Singh (Co-Organizer at GDG Noida, Design Lead at Publicis Sapient) Aryendra presented Jakob Nielsen’s 10 Usability Heuristics, providing practical advice on applying these principles to create intuitive and user-friendly products.
Introduction to Project IDX and Firebase Genkit | Build an Agent-Powered App with Generative AI
Attendees were introduced to Google’s latest tools, Project IDX and Firebase Genkit, which facilitate the development of AI-powered applications. This session showcased how to build apps that integrate Generative AI, offering new ways to enhance app functionality.
Networking & Swag Distribution
The event concluded with a networking session, where participants had the opportunity to engage with speakers and fellow developers. Google swag was distributed, adding a fun and memorable touch to the end of the day.
Conclusion
Google I/O Extended Lucknow 2023 was a highly informative and engaging event. Attendees gained valuable insights into containers, AI integration, product design, and usability, all while building stronger connections within the local developer community.
diff --git a/_site/docs/layout/Events & Meetups/layout/index.html b/_site/docs/layout/Events & Meetups/layout/index.html
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To start studying AI, begin by learning programming languages like Python, as it’s commonly used in AI development. You can also take online courses in AI, machine learning, and data science from platforms like Coursera, edX, or Udemy. Start with the basics of algorithms, data structures, and AI fundamentals.
Q: How can I apply AI to real-world problems?
Once you’ve learned the fundamentals, try applying AI to real-world problems by building projects such as a chatbot, image classifier, or recommendation system. You can also participate in Kaggle competitions or contribute to open-source AI projects to gain experience.
Q: What are the career opportunities in AI?
AI offers a wide range of career opportunities, including roles like AI engineer, data scientist, machine learning engineer, NLP specialist, and AI research scientist. Many industries, from healthcare to finance, are actively looking for AI talent to help build intelligent systems.
Q: What are the best online courses to learn AI?
Some of the best online courses include:
Coursera: "Machine Learning" by Andrew Ng, "Deep Learning Specialization" by DeepLearning.AI
edX: "Introduction to Artificial Intelligence" from MIT
Udemy: "Artificial Intelligence A-Z™: Learn How to Build an AI"
Fast.ai: Practical deep learning courses designed for beginners.
Q: How important is math for learning AI?
Mathematics is essential for understanding the algorithms behind AI. Linear algebra, probability, statistics, and calculus are particularly important in areas like machine learning and deep learning. However, many practical AI tools and libraries abstract the math, allowing you to start building without deep mathematical knowledge.
diff --git a/_site/docs/layout/FAQ/FAQs/index.html b/_site/docs/layout/FAQ/FAQs/index.html
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Lucknow AI Labs is a nonprofit organization dedicated to growing awareness about artificial intelligence (AI) and its applications. We focus on educating individuals, businesses, and communities on AI technologies while providing hands-on learning opportunities and resources.
Q: Who can benefit from Lucknow AI Labs’ programs?
Our programs are open to students, developers, entrepreneurs, and professionals from all industries who are interested in learning more about AI. We welcome anyone who wants to explore how AI can improve their skills or help their organization.
Q: How is Lucknow AI Labs funded?
As a nonprofit, we rely on donations, grants, and sponsorships to fund our activities. We also collaborate with educational institutions and other organizations to support our mission of spreading AI knowledge.
Q: How does Lucknow AI Labs ensure inclusivity in AI education?
We are committed to making AI education accessible to everyone, regardless of their background. Our workshops and events are designed to be inclusive, with resources for beginners and opportunities for underserved communities to learn about AI.
Q: How can I support Lucknow AI Labs?
You can support us by volunteering, donating, or participating in our events and workshops. Additionally, sharing our mission and helping spread AI awareness in your community contributes to our cause.
diff --git a/_site/docs/layout/FAQ/Volunteer FAQs/index.html b/_site/docs/layout/FAQ/Volunteer FAQs/index.html
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+ Volunteer FAQs | Lucknow AISkip to main content
You can volunteer by filling out the application form on our website or by contacting us directly via email. We welcome individuals with a passion for AI, education, and community outreach to join our mission of spreading AI awareness.
Q: Do I need AI or technical expertise to volunteer?
While having AI or technical expertise is beneficial for certain roles, it is not a requirement for all volunteer positions. We also need volunteers for administrative tasks, event organization, outreach, and content creation. We provide training and guidance to help volunteers succeed in their roles.
Q: What is the time commitment for volunteering?
The time commitment varies depending on the role. Some volunteer positions may require a few hours a week, while others may be more involved during specific events or projects. We are flexible and will work with you to find a commitment level that suits your schedule.
Q: Can I volunteer remotely?
Yes, many of our volunteer opportunities, such as content creation, social media management, and technical support, can be done remotely. We strive to make volunteering accessible to people from all locations.
Q: What are the benefits of volunteering with Lucknow AI Labs?
Volunteering with Lucknow AI Labs gives you the chance to contribute to AI awareness, develop your skills, and gain experience working in a nonprofit focused on cutting-edge technology. You’ll also have the opportunity to network with AI professionals and make a positive impact in your community.
Q: Will I receive training or support as a volunteer?
Yes, we provide training and guidance to all volunteers, especially for roles that require specific skills. Our team will support you throughout your volunteering journey, ensuring you feel confident and equipped to contribute effectively.
Q: Can I volunteer if I’m a student?
Absolutely! We encourage students to volunteer as it’s a great way to learn more about AI and gain hands-on experience. Whether you're studying AI, computer science, or any other field, we have opportunities that will allow you to contribute meaningfully.
diff --git a/_site/docs/layout/layout/index.html b/_site/docs/layout/layout/index.html
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--- a/_site/docs/layout/layout/index.html
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- Events & Meetups | Lucknow AISkip to main content
This is a child page that uses the same minimal layout as its parent page.
diff --git a/_site/docs/layout/projects/final_year_project/index.html b/_site/docs/layout/projects/final_year_project/index.html
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+ Final Year Project Generator | Lucknow AISkip to main content
Markdown does not include support for callouts. However, you can style text as a callout using a Markdown extension supported by kramdown: block IALs.
Common kinds of callouts include highlight, important, new, note, and warning.
These callout names are not pre-defined by the theme: you need to define your own names.
When you have configured the color and (optional) title for a callout, you can apply it to a paragraph, or to a block quote with several paragraphs, as illustrated below.1
Markdown does not include support for callouts. However, you can style text as a callout using a Markdown extension supported by kramdown: block IALs.
Common kinds of callouts include highlight, important, new, note, and warning.
These callout names are not pre-defined by the theme: you need to define your own names.
When you have configured the color and (optional) title for a callout, you can apply it to a paragraph, or to a block quote with several paragraphs, as illustrated below.1
An untitled callout
{: .highlight }
A paragraph
A paragraph
A single paragraph callout
{: .note }
A paragraph
diff --git a/_site/docs/ui-components/code/index.html b/_site/docs/ui-components/code/index.html
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--- a/_site/docs/ui-components/code/index.html
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- Code | Lucknow AISkip to main content
Code can be rendered inline by wrapping it in single back ticks.
Lorem ipsum dolor sit amet, <inline code snippet> adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Heading with <inline code snippet> in it.
Lorem ipsum dolor sit amet, `<inline code snippet>` adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
+ Code | Lucknow AISkip to main content
Code can be rendered inline by wrapping it in single back ticks.
Lorem ipsum dolor sit amet, <inline code snippet> adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Heading with <inline code snippet> in it.
Lorem ipsum dolor sit amet, `<inline code snippet>` adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
## Heading with `<inline code snippet>` in it.
Syntax highlighted code blocks
Use Jekyll’s built-in syntax highlighting with Rouge for code blocks by using three backticks, followed by the language name:
// Javascript code with syntax highlighting.
diff --git a/_site/docs/ui-components/code/line-numbers/index.html b/_site/docs/ui-components/code/line-numbers/index.html
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The default settings for HTML compression are incompatible with the HTML produced by Jekyll (4.1.1 or earlier) for line numbers from highlighted code – both when using Kramdown code fences and when using Liquid highlight tags.
To avoid non-conforming HTML and unsatisfactory layout, HTML compression can be turned off by using the following configuration option:
The default settings for HTML compression are incompatible with the HTML produced by Jekyll (4.1.1 or earlier) for line numbers from highlighted code – both when using Kramdown code fences and when using Liquid highlight tags.
To avoid non-conforming HTML and unsatisfactory layout, HTML compression can be turned off by using the following configuration option:
compress_html:ignore:envs:all
When using Kramdown code fences, line numbers are turned on globally by the following configuration option:
kramdown:syntax_highlighter_opts:
diff --git a/_site/docs/ui-components/labels/index.html b/_site/docs/ui-components/labels/index.html
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- Labels | Lucknow AISkip to main content
Tables are responsive by default, allowing wide tables to have a horizontal scroll to access columns outside of the normal viewport.
head1
head two
three
ok
good swedish fish
nice
out of stock
good and plenty
nice
ok
good oreos
hmm
ok
good zoute drop
yumm
| head1 | head two | three |
|:-------------|:------------------|:------|
| ok | good swedish fish | nice |
| out of stock | good and plenty | nice |
diff --git a/_site/docs/ui-components/typography/index.html b/_site/docs/ui-components/typography/index.html
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The LAI Labs Mentorship Program connects experienced AI professionals with aspiring learners for collaborative project development, research, and skill enhancement.
Enrollment Process
Visit the LAI Labs website and navigate to the Mentorship Program section.
Fill out the application form specifying if you're applying as a mentor or mentee.
Mentees: Describe your background, goals, and areas of interest in AI.
Mentors: Detail your expertise, experience, and mentorship philosophy.
Benefits
For Mentees:
Personalized guidance from industry experts
Hands-on experience with real-world AI projects
Networking within the AI community
Skill development in cutting-edge AI technologies
For Mentors:
Opportunity to give back to the community
Recognition as a thought leader in AI
Enhancement of leadership and communication skills
Mentor Guidelines
Ensure that all mentor-mentee interactions adhere to the LAI Labs standards.
Communication Channels
Use official platforms like Discord and Google Meet for all interactions.
Session Structure
Weekly one-hour sessions (minimum)
Additional asynchronous communication through Discord
Responsibilities
Provide expert guidance in AI concepts and technologies
Assist in project planning and execution
Offer career advice and industry insights
Mentee Guidelines
Mentees are expected to be committed and proactive during the mentorship period.
Program Commitment
Attend all scheduled sessions with your mentor
Dedicate at least 5 hours per week to program-related work
Project Requirements
Develop a project proposal within the first two weeks
Provide weekly progress updates
Present your final project at the end of the program
All the colors used in Just the Docs have been systematized into a series of variables that have been extended to both font color and background color utility classes.
All the colors used in Just the Docs have been systematized into a series of variables that have been extended to both font color and background color utility classes.
Light Greys
Color value
Font color utility
Background color utility
grey-lt-000
.text-grey-lt-000
.bg-grey-lt-000
grey-lt-100
.text-grey-lt-100
.bg-grey-lt-100
grey-lt-200
.text-grey-lt-200
.bg-grey-lt-200
grey-lt-300
.text-grey-lt-300
.bg-grey-lt-300
Dark Greys
Color value
Font color utility
Background color utility
grey-dk-000
.text-grey-dk-000
.bg-grey-dk-000
grey-dk-100
.text-grey-dk-100
.bg-grey-dk-100
grey-dk-200
.text-grey-dk-200
.bg-grey-dk-200
grey-dk-250
.text-grey-dk-250
.bg-grey-dk-250
grey-dk-300
.text-grey-dk-300
.bg-grey-dk-300
Purples
Color value
Font color utility
Background color utility
purple-000
.text-purple-000
.bg-purple-000
purple-100
.text-purple-100
.bg-purple-100
purple-200
.text-purple-200
.bg-purple-200
purple-300
.text-purple-300
.bg-purple-300
Blues
Color value
Font color utility
Background color utility
blue-000
.text-blue-000
.bg-blue-000
blue-100
.text-blue-100
.bg-blue-100
blue-200
.text-blue-200
.bg-blue-200
blue-300
.text-blue-300
.bg-blue-300
Greens
Color value
Font color utility
Background color utility
green-000
.text-green-000
.bg-green-000
green-100
.text-green-100
.bg-green-100
green-200
.text-green-200
.bg-green-200
green-300
.text-green-300
.bg-green-300
Yellows
Color value
Font color utility
Background color utility
yellow-000
.text-yellow-000
.bg-yellow-000
yellow-100
.text-yellow-100
.bg-yellow-100
yellow-200
.text-yellow-200
.bg-yellow-200
yellow-300
.text-yellow-300
.bg-yellow-300
Reds
Color value
Font color utility
Background color utility
red-000
.text-red-000
.bg-red-000
red-100
.text-red-100
.bg-red-100
red-200
.text-red-200
.bg-red-200
red-300
.text-red-300
.bg-red-300
diff --git a/_site/docs/utilities/layout/index.html b/_site/docs/utilities/layout/index.html
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These spacers are available to use for margins and padding with responsive utility classes. Combine these prefixes with a screen size and spacing scale to use them responsively.
Classname prefix
What it does
.m-
margin
.mx-
margin-left, margin-right
.my-
margin top, margin bottom
.mt-
margin-top
.mr-
margin-right
.mb-
margin-bottom
.ml-
margin-left
Classname prefix
What it does
.p-
padding
.px-
padding-left, padding-right
.py-
padding top, padding bottom
.pt-
padding-top
.pr-
padding-right
.pb-
padding-bottom
.pl-
padding-left
Spacing values are based on a 1rem = 16px spacing scale, broken down into these units:
Spacer/suffix
Size in rems
Rem converted to px
1
0.25rem
4px
2
0.5rem
8px
3
0.75rem
12px
4
1rem
16px
5
1.5rem
24px
6
2rem
32px
7
2.5rem
40px
8
3rem
48px
auto
auto
auto
Use mx-auto to horizontally center elements.
Examples
In Markdown, use the {: } wrapper to apply custom classes:
This paragraph will have a margin bottom of 1rem/16px on large screens.
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These spacers are available to use for margins and padding with responsive utility classes. Combine these prefixes with a screen size and spacing scale to use them responsively.
Classname prefix
What it does
.m-
margin
.mx-
margin-left, margin-right
.my-
margin top, margin bottom
.mt-
margin-top
.mr-
margin-right
.mb-
margin-bottom
.ml-
margin-left
Classname prefix
What it does
.p-
padding
.px-
padding-left, padding-right
.py-
padding top, padding bottom
.pt-
padding-top
.pr-
padding-right
.pb-
padding-bottom
.pl-
padding-left
Spacing values are based on a 1rem = 16px spacing scale, broken down into these units:
Spacer/suffix
Size in rems
Rem converted to px
1
0.25rem
4px
2
0.5rem
8px
3
0.75rem
12px
4
1rem
16px
5
1.5rem
24px
6
2rem
32px
7
2.5rem
40px
8
3rem
48px
auto
auto
auto
Use mx-auto to horizontally center elements.
Examples
In Markdown, use the {: } wrapper to apply custom classes:
This paragraph will have a margin bottom of 1rem/16px on large screens.
{: .mb-lg-4 }
This paragraph will have 2rem/32px of padding on the right and left at all screen sizes.
diff --git a/_site/docs/utilities/responsive-modifiers/index.html b/_site/docs/utilities/responsive-modifiers/index.html
index 0eef41b9..f2dad2bf 100644
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@@ -1 +1 @@
- Responsive Modifiers | Lucknow AISkip to main content
Just the Docs spacing works in conjunction with a variety of modifiers that allow you to target specific screen sizes responsively. Use these in conjunction with spacing and display prefix and suffix classes.
Just the Docs spacing works in conjunction with a variety of modifiers that allow you to target specific screen sizes responsively. Use these in conjunction with spacing and display prefix and suffix classes.
Modifier
Screen size
(none)
All screens until the next modifier
xs
320px (20rem) and up
sm
500px (31.25rem) and up
md
740px (46.25rem) and up
lg
1120px (70rem) and up
xl
1400px (87.5rem) and up
diff --git a/_site/docs/utilities/typography/index.html b/_site/docs/utilities/typography/index.html
index bdb267a0..5658da4b 100644
--- a/_site/docs/utilities/typography/index.html
+++ b/_site/docs/utilities/typography/index.html
@@ -1,4 +1,4 @@
- Typography | Lucknow AISkip to main content
Use the .fs-1 - .fs-10 to set an explicit font-size.
Class
Small screen size font-size
Large screen size font-size
.fs-1
9px
10px
.fs-2
11px
12px
.fs-3
12px
14px
.fs-4
14px
16px
.fs-5
16px
18px
.fs-6
18px
24px
.fs-7
24px
32px
.fs-8
32px
38px
.fs-9
38px
42px
.fs-10
42px
48px
Font size 1
Font size 2
Font size 3
Font size 4
Font size 5
Font size 6
Font size 7
Font size 8
Font size 9
Font size 10
In Markdown, use the `{: }` wrapper to apply custom classes:
Font size 1
{: .fs-1 }
diff --git a/_site/index.html b/_site/index.html
index 70aff641..4edb5452 100644
--- a/_site/index.html
+++ b/_site/index.html
@@ -1 +1 @@
- Home | Lucknow AISkip to main content
When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change. Read more about becoming a contributor in our GitHub repo.
Thank you to the contributors of Lucknow AI!
Code of Conduct
Lucknow AI is committed to fostering a welcoming community.
When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change. Read more about becoming a contributor in our GitHub repo.
Thank you to the contributors of Lucknow AI!
Code of Conduct
Lucknow AI is committed to fostering a welcoming community.
-
-## 1. Project Awadhi
-
-This project focuses on developing localized solutions using advanced AI and machine learning techniques.
-
-## 2. Lallan
-
-- [Lallan - Lucknow Artificial Language and Learning Assistance Network](/projects/lallan)
-
-[Try Lallan](/projects/lallan){: .btn .btn-primary .fs-5 .mb-4 .mb-md-0 .mr-2 }
-
-## 3. Project Sign Language
-This project focuses on developing localized solutions using advanced AI and machine learning techniques.
\ No newline at end of file
diff --git a/docs/layout/10-Aug-2024 Discord AMA.md b/docs/layout/Events & Meetups/10-Aug-2024 Discord AMA.md
similarity index 100%
rename from docs/layout/10-Aug-2024 Discord AMA.md
rename to docs/layout/Events & Meetups/10-Aug-2024 Discord AMA.md
diff --git a/docs/layout/13-Jan-2024-Jaime_voice _assistant.md b/docs/layout/Events & Meetups/13-Jan-2024-Jaime_voice _assistant.md
similarity index 100%
rename from docs/layout/13-Jan-2024-Jaime_voice _assistant.md
rename to docs/layout/Events & Meetups/13-Jan-2024-Jaime_voice _assistant.md
diff --git a/docs/layout/21-Jan-24-Startup_Success_days_GdgLko.md b/docs/layout/Events & Meetups/21-Jan-24-Startup_Success_days_GdgLko.md
similarity index 100%
rename from docs/layout/21-Jan-24-Startup_Success_days_GdgLko.md
rename to docs/layout/Events & Meetups/21-Jan-24-Startup_Success_days_GdgLko.md
diff --git a/docs/layout/23-24-May-2024-Hack-To-Crack-1.md b/docs/layout/Events & Meetups/23-24-May-2024-Hack-To-Crack-1.md
similarity index 100%
rename from docs/layout/23-24-May-2024-Hack-To-Crack-1.md
rename to docs/layout/Events & Meetups/23-24-May-2024-Hack-To-Crack-1.md
diff --git a/docs/layout/25-May-2024 GenAI Awadh.md b/docs/layout/Events & Meetups/25-May-2024 GenAI Awadh.md
similarity index 100%
rename from docs/layout/25-May-2024 GenAI Awadh.md
rename to docs/layout/Events & Meetups/25-May-2024 GenAI Awadh.md
diff --git a/docs/layout/26-nov-2023-meetup.md b/docs/layout/Events & Meetups/26-nov-2023-meetup.md
similarity index 100%
rename from docs/layout/26-nov-2023-meetup.md
rename to docs/layout/Events & Meetups/26-nov-2023-meetup.md
diff --git a/docs/layout/27-Apr-2024 GDSC WOW.md b/docs/layout/Events & Meetups/27-Apr-2024 GDSC WOW.md
similarity index 100%
rename from docs/layout/27-Apr-2024 GDSC WOW.md
rename to docs/layout/Events & Meetups/27-Apr-2024 GDSC WOW.md
diff --git a/docs/layout/27-Feb-2024 AI Workshop at SRMCEM.md b/docs/layout/Events & Meetups/27-Feb-2024 AI Workshop at SRMCEM.md
similarity index 100%
rename from docs/layout/27-Feb-2024 AI Workshop at SRMCEM.md
rename to docs/layout/Events & Meetups/27-Feb-2024 AI Workshop at SRMCEM.md
diff --git a/docs/layout/27-Jan-2024-Image_Processing_and_OpenCV_Webinar.md b/docs/layout/Events & Meetups/27-Jan-2024-Image_Processing_and_OpenCV_Webinar.md
similarity index 100%
rename from docs/layout/27-Jan-2024-Image_Processing_and_OpenCV_Webinar.md
rename to docs/layout/Events & Meetups/27-Jan-2024-Image_Processing_and_OpenCV_Webinar.md
diff --git a/docs/layout/29-Jun-2024 Build with AI.md b/docs/layout/Events & Meetups/29-Jun-2024 Build with AI.md
similarity index 100%
rename from docs/layout/29-Jun-2024 Build with AI.md
rename to docs/layout/Events & Meetups/29-Jun-2024 Build with AI.md
diff --git a/docs/layout/31-Aug-2024 Google IO Extend.md b/docs/layout/Events & Meetups/31-Aug-2024 Google IO Extend.md
similarity index 100%
rename from docs/layout/31-Aug-2024 Google IO Extend.md
rename to docs/layout/Events & Meetups/31-Aug-2024 Google IO Extend.md
diff --git a/docs/layout/layout.md b/docs/layout/Events & Meetups/layout.md
similarity index 100%
rename from docs/layout/layout.md
rename to docs/layout/Events & Meetups/layout.md
diff --git a/docs/layout/FAQ/Commonly Asked Questions.md b/docs/layout/FAQ/Commonly Asked Questions.md
new file mode 100644
index 00000000..dbf3a762
--- /dev/null
+++ b/docs/layout/FAQ/Commonly Asked Questions.md
@@ -0,0 +1,131 @@
+---
+title: Commonly Asked Questions
+parent: FAQs
+layout: default
+nav_order: 2
+---
+
+
Frequently Asked Questions
+
+
+
+
Q: How can I start studying AI?
+
+
To start studying AI, begin by learning programming languages like Python, as it’s commonly used in AI development. You can also take online courses in AI, machine learning, and data science from platforms like Coursera, edX, or Udemy. Start with the basics of algorithms, data structures, and AI fundamentals.
+
+
+
+
+
Q: How can I apply AI to real-world problems?
+
+
Once you’ve learned the fundamentals, try applying AI to real-world problems by building projects such as a chatbot, image classifier, or recommendation system. You can also participate in Kaggle competitions or contribute to open-source AI projects to gain experience.
+
+
+
+
+
Q: What are the career opportunities in AI?
+
+
AI offers a wide range of career opportunities, including roles like AI engineer, data scientist, machine learning engineer, NLP specialist, and AI research scientist. Many industries, from healthcare to finance, are actively looking for AI talent to help build intelligent systems.
+
+
+
+
+
Q: What are the best online courses to learn AI?
+
+
Some of the best online courses include:
+
+
Coursera: "Machine Learning" by Andrew Ng, "Deep Learning Specialization" by DeepLearning.AI
+
edX: "Introduction to Artificial Intelligence" from MIT
+
Udemy: "Artificial Intelligence A-Z™: Learn How to Build an AI"
+
Fast.ai: Practical deep learning courses designed for beginners.
+
+
+
+
+
+
Q: How important is math for learning AI?
+
+
Mathematics is essential for understanding the algorithms behind AI. Linear algebra, probability, statistics, and calculus are particularly important in areas like machine learning and deep learning. However, many practical AI tools and libraries abstract the math, allowing you to start building without deep mathematical knowledge.
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/layout/FAQ/FAQs.md b/docs/layout/FAQ/FAQs.md
new file mode 100644
index 00000000..80078408
--- /dev/null
+++ b/docs/layout/FAQ/FAQs.md
@@ -0,0 +1,6 @@
+---
+title: FAQs
+layout: default
+nav_order: 10
+has_children: true
+---
\ No newline at end of file
diff --git a/docs/layout/FAQ/LAI FAQs.md b/docs/layout/FAQ/LAI FAQs.md
new file mode 100644
index 00000000..217fee87
--- /dev/null
+++ b/docs/layout/FAQ/LAI FAQs.md
@@ -0,0 +1,126 @@
+---
+title: LAI FAQs
+parent: FAQs
+layout: default
+nav_order: 1
+---
+
+
+
Frequently Asked Questions
+
+
+
+
Q: What is Lucknow AI Labs?
+
+
Lucknow AI Labs is a nonprofit organization dedicated to growing awareness about artificial intelligence (AI) and its applications. We focus on educating individuals, businesses, and communities on AI technologies while providing hands-on learning opportunities and resources.
+
+
+
+
+
Q: Who can benefit from Lucknow AI Labs’ programs?
+
+
Our programs are open to students, developers, entrepreneurs, and professionals from all industries who are interested in learning more about AI. We welcome anyone who wants to explore how AI can improve their skills or help their organization.
+
+
+
+
+
Q: How is Lucknow AI Labs funded?
+
+
As a nonprofit, we rely on donations, grants, and sponsorships to fund our activities. We also collaborate with educational institutions and other organizations to support our mission of spreading AI knowledge.
+
+
+
+
+
Q: How does Lucknow AI Labs ensure inclusivity in AI education?
+
+
We are committed to making AI education accessible to everyone, regardless of their background. Our workshops and events are designed to be inclusive, with resources for beginners and opportunities for underserved communities to learn about AI.
+
+
+
+
+
Q: How can I support Lucknow AI Labs?
+
+
You can support us by volunteering, donating, or participating in our events and workshops. Additionally, sharing our mission and helping spread AI awareness in your community contributes to our cause.
You can volunteer by filling out the application form on our website or by contacting us directly via email. We welcome individuals with a passion for AI, education, and community outreach to join our mission of spreading AI awareness.
+
+
+
+
+
Q: Do I need AI or technical expertise to volunteer?
+
+
While having AI or technical expertise is beneficial for certain roles, it is not a requirement for all volunteer positions. We also need volunteers for administrative tasks, event organization, outreach, and content creation. We provide training and guidance to help volunteers succeed in their roles.
+
+
+
+
+
+
+
Q: What is the time commitment for volunteering?
+
+
The time commitment varies depending on the role. Some volunteer positions may require a few hours a week, while others may be more involved during specific events or projects. We are flexible and will work with you to find a commitment level that suits your schedule.
+
+
+
+
+
Q: Can I volunteer remotely?
+
+
Yes, many of our volunteer opportunities, such as content creation, social media management, and technical support, can be done remotely. We strive to make volunteering accessible to people from all locations.
+
+
+
+
+
Q: What are the benefits of volunteering with Lucknow AI Labs?
+
+
Volunteering with Lucknow AI Labs gives you the chance to contribute to AI awareness, develop your skills, and gain experience working in a nonprofit focused on cutting-edge technology. You’ll also have the opportunity to network with AI professionals and make a positive impact in your community.
+
+
+
+
+
Q: Will I receive training or support as a volunteer?
+
+
Yes, we provide training and guidance to all volunteers, especially for roles that require specific skills. Our team will support you throughout your volunteering journey, ensuring you feel confident and equipped to contribute effectively.
+
+
+
+
+
Q: Can I volunteer if I’m a student?
+
+
Absolutely! We encourage students to volunteer as it’s a great way to learn more about AI and gain hands-on experience. Whether you're studying AI, computer science, or any other field, we have opportunities that will allow you to contribute meaningfully.
+
+
+
+
+
+
+
+
+
diff --git a/docs/layout/projects/final_year_project.md b/docs/layout/projects/final_year_project.md
new file mode 100644
index 00000000..4799ce43
--- /dev/null
+++ b/docs/layout/projects/final_year_project.md
@@ -0,0 +1,9 @@
+---
+title: Final Year Project Generator
+parent: Projects
+layout: default
+nav_order: 2
+---
+
+# Final Year Project Generator
+
diff --git a/docs/layout/projects/nawabAI.md b/docs/layout/projects/nawabAI.md
new file mode 100644
index 00000000..d926e662
--- /dev/null
+++ b/docs/layout/projects/nawabAI.md
@@ -0,0 +1,11 @@
+---
+layout: default
+parent: Projects
+title: NAWAB AI
+nav_order: 1
+---
+
+# Nawab AI
+
+## Nawab AI
+
diff --git a/docs/layout/projects/projects.md b/docs/layout/projects/projects.md
new file mode 100644
index 00000000..242dc53f
--- /dev/null
+++ b/docs/layout/projects/projects.md
@@ -0,0 +1,21 @@
+---
+layout: default
+title: Projects
+nav_order: 4
+has_children: true
+has_toc: false
+---
+
+
+# Community Projects
+
+## Completed Projects
+
+Currently, there are no completed projects to showcase.
+
+## Ongoing Projects
+
+| Project Name | Description |
+|-----------------------------|--------------------------------------------------------------------------------------------------------------|
+| [NAWAB AI](/docs/layout/projects/nawabAI/) | An application for the people of Lucknow where they can find news, map locations, and a personalized chat assistant to guide them in the city. |
+| [Final Year Project Generator](/docs/layout/projects/finalYearProjectGenerator/) | A tool for students in their final year of college, helping them generate and refine ideas for their final year projects. |
diff --git a/docs/ui-components/ui-components.md b/docs/ui-components/ui-components.md
index 9c38e941..50bdf0a7 100644
--- a/docs/ui-components/ui-components.md
+++ b/docs/ui-components/ui-components.md
@@ -2,6 +2,8 @@
layout: default
title: Research & Publications
nav_order: 3
-has_children: true
+has_children: false
permalink: /docs/ui-components
----
\ No newline at end of file
+---
+
+# Coming Soon
\ No newline at end of file
diff --git a/docs/utilities/utilities.md b/docs/utilities/utilities.md
index 9690fad3..008218c1 100644
--- a/docs/utilities/utilities.md
+++ b/docs/utilities/utilities.md
@@ -1,9 +1,123 @@
---
layout: default
-title: Mentorship Program
-nav_order: 5
-has_children: true
+title: LAI Mentorship Program
+nav_order: 7
+has_children: false
permalink: docs/utilities
---
{: .fs-6 .fw-300 }
+
+
+
+
LAI Labs Mentorship Program
+
Fostering growth, innovation, and knowledge sharing between experienced AI professionals and aspiring learners.
The LAI Labs Mentorship Program connects experienced AI professionals with aspiring learners for collaborative project development, research, and skill enhancement.
+
+
Enrollment Process
+
+
Visit the LAI Labs website and navigate to the Mentorship Program section.
+
Fill out the application form specifying if you're applying as a mentor or mentee.
+
Mentees: Describe your background, goals, and areas of interest in AI.
+
Mentors: Detail your expertise, experience, and mentorship philosophy.
+
+
+
Benefits
+
+
+
For Mentees:
+
+
Personalized guidance from industry experts
+
Hands-on experience with real-world AI projects
+
Networking within the AI community
+
Skill development in cutting-edge AI technologies
+
+
+
+
For Mentors:
+
+
Opportunity to give back to the community
+
Recognition as a thought leader in AI
+
Enhancement of leadership and communication skills
+
+
+
+
+
+
+
+
+
+
Mentor Guidelines
+
Ensure that all mentor-mentee interactions adhere to the LAI Labs standards.
+
+
Communication Channels
+
Use official platforms like Discord and Google Meet for all interactions.
+
+
Session Structure
+
+
Weekly one-hour sessions (minimum)
+
Additional asynchronous communication through Discord
+
+
+
Responsibilities
+
+
Provide expert guidance in AI concepts and technologies
+
Assist in project planning and execution
+
Offer career advice and industry insights
+
+
+
+
+
+
+
+
Mentee Guidelines
+
Mentees are expected to be committed and proactive during the mentorship period.
+
+
Program Commitment
+
+
Attend all scheduled sessions with your mentor
+
Dedicate at least 5 hours per week to program-related work
+
+
+
Project Requirements
+
+
Develop a project proposal within the first two weeks
+
Provide weekly progress updates
+
Present your final project at the end of the program
Source: https://gdglucknow.web.app