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A curated list of awesome open source and commercial MLOps platforms πŸš€

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awesome-mlops-platforms

A curated list of awesome open source and commercial MLOps platforms πŸš€

  • ClearML: Auto-Magical experiment manager and version control for AI (previously Trains).
  • CNVRG: An end-to-end machine learning platform to build and deploy AI models at scale.
  • DAGsHub: A platform built on open source tools for data, model and pipeline management.
  • Dataiku: Platform democratizing access to data and enabling enterprises to build their own path to AI.
  • DataRobot: AI platform that democratizes data science and automates the end-to-end ML at scale.
  • Domino: One place for your data science tools, apps, results, models, and knowledge.
  • Determined: Deep learning training platform with integrated support for distributed training, hyperparameter tuning, and model management (supports Tensorflow and Pytorch).
  • Flyte: A cloud native machine learning and data processing platform.
  • Gradient: Multicloud CI/CD and MLOps platform for machine learning teams.
  • H2O: Open source leader in AI with a mission to democratize AI for everyone.
  • Hopsworks: Open-source platform for developing and operating machine learning models at scale.
  • Iguazio: Data science platform that automates MLOps with end-to-end machine learning pipelines.
  • Knime: Create and productionize data science using one easy and intuitive environment.
  • Kubeflow: A machine learning toolkit for Kubernetes.
  • MLRun: A framework that offers an integrative approach to managing your machine-learning pipelines from early development through model development to full pipeline deployment in production.
  • Onepanel: Production scale vision AI platform, with fully integrated components for model building, automated labeling, data processing and model training pipelines.
  • Open Platform for AI: Platform that provides complete AI model training and resource management capabilities.
  • Pachyderm: Open source distributed processing framework build on Kubernetes focused mainly on dynamic building of production machine learning pipelines.
  • Polyaxon: A cloud native machine learning management & orchestration platform.
  • Sagemaker: Fully managed service that provides the ability to build, train, and deploy ML models quickly.
  • Valohai: Takes you from POC to production while managing the whole model lifecycle.
  • ZenML: An extensible, open-source MLOps framework to create reproducible ML pipelines with a focus on automated metadata tracking, caching, and many integrations to other tools.