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awesome-experiment-tracking

Curated list of available experiment tracking frameworks
https://github.com/roma-glushko/awesome-experiment-tracking

  • Aim - logs your training runs, enables a beautiful UI to compare them and an API to query them programmatically
  • Sacred - configure, organize, log and reproduce experiments
  • Kedro - open-source Python framework for creating reproducible, maintainable and modular data science code based on software engineering principles like modularity, separation of concerns and versioning
  • ClearML - a ML/DL development and production suite, it contains 4 main modules: Experiment Manager, MLOps, Data Management, Model Serving.
  • Polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning Lifecycle
  • Keepsake - Version control for machine learning
  • MLFlow - Open source platform for the machine learning lifecycle
  • GuildAI - brings systematic control to machine learning to help you build better models faster
  • TensorBoard - provides the visualization and tooling needed for machine learning experimentation
  • DVC - Version Control System for Machine Learning Projects
  • Weights & Biases - Build better models faster with experiment tracking, dataset versioning, and model management
  • Neptune.ai - Experiment tracking and model registry for production teams
  • Comet ML - Manage and optimize the entire ML lifecycle, from experiment tracking to model production monitoring