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awesome-ml-experiment-management

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About awesome-ml-experiment-management

# awesome-ml-experiment-management A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀 * [Aim](https://github.com/aimhubio/aim): An easy-to-use and performant open-source experiment tracker. * [ClearML](https://github.com/allegroai/clearml): Automagical experiment tracking, environments and results * [Comet](https://www.comet.ml/): Manage and optimize the entire ML lifecycle, from experiment tracking to model production monitoring. * [DVC Studio](https://studio.iterative.ai/): A web application that works with the data, metrics and hyperparameters that you add to your ML project repositories. * [Guild AI](https://guild.ai/): Open source experiment tracking, pipeline automation, and hyperparameter tuning. * [Keepsake](https://github.com/replicate/keepsake): Version control for machine learning with support to Amazon S3 and Google Cloud Storage. * [mlflow](https://github.com/mlflow/mlflow): Open source platform for the machine learning lifecy ...

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Web Self-hosted Kubernetes

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awesome-ml-experiment-management

A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀

  • Aim: An easy-to-use and performant open-source experiment tracker.
  • ClearML: Automagical experiment tracking, environments and results
  • Comet: Manage and optimize the entire ML lifecycle, from experiment tracking to model production monitoring.
  • DVC Studio: A web application that works with the data, metrics and hyperparameters that you add to your ML project repositories.
  • Guild AI: Open source experiment tracking, pipeline automation, and hyperparameter tuning.
  • Keepsake: Version control for machine learning with support to Amazon S3 and Google Cloud Storage.
  • mlflow: Open source platform for the machine learning lifecycle.
  • Neptune: A lightweight experiment management tool that fits any workflow.
  • Polyaxon: Open-source ML experiemnts management platform.
  • Sacred: A tool to configure, organize, log and reproduce computational experiments.
  • Tensorboard: Provides the visualization and tooling needed for machine learning experimentation.
  • TraceML: Engine for ML/Data tracking, visualization, dashboards, and model UI.
  • Weights and Biases: A tool for visualizing and tracking your machine learning experiments.