A record of my studies on Machine Learning, Deep Learning, and Artificial Intelligence in general.
The primary aim of maintaining this repository is to track my progress, reflect on my learning curve, and share my studies with the community. I hope to inspire fellow programmers to embark on their Data Science journeys and provide a resource for those seeking knowledge or verification of their approaches.
I intend to update this repository as I organize more studies that can be made public. As each project needs to have its own notebook with some theory and the step-by-step process, this can take some time.
Each folder contains a different project, each project contains its own Jupyter notebook with details about the project, theory and code.
It's recommended to use anaconda3, micromamba or any other Python environment
management system. You can setup the environment by running
conda env create -f environment.yml and you're good to go. This environment
should be enough to run all the projects in this repository.
- Some of the notebooks in this repository were based on the Supervised Machine Learning course by Coursera;
- Some of the notebooks were based on classes I took at the University of Brasília, thank you Paulo Henrique Portela de Carvalho for the excellent work;
Some of the projects were originally written in portuguese (as per external requirements), but were later translated to english by me. Moreover, some of the code is not perfect, but keep in mind this repository is a work in progress.
MIT License
GitHub @akaTsunemori