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21 Experiment Management and Version Control Tools for AI Development and Reproducibility

Discover open source tools for experiment management and version control to enhance AI development and reproducibility.

Open Source Experiment Management Tools

  • Aim

    A super-easy way to record, search and compare AI experiments.

    License: Apache License 2.0

  • Catalyst

    High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing.

    License: Apache License 2.0

  • ClearML

    Auto-Magical Experiment Manager & Version Control for AI (previously Trains).

    License: Apache License 2.0

  • CodaLab

    CodaLab Worksheets is a collaborative platform for reproducible research that allows researchers to run, manage, and share their experiments in the cloud. It helps researchers ensure that their runs are reproducible and consistent.

    License: Other

  • Data Version Control (DVC)

    A git fork that allows for version management of models.

    License: Apache License 2.0

  • Deepkit

    An open-source platform and cross-platform desktop application to execute, track, and debug modern machine learning experiments.

    License: MIT License

  • Dolt

    Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a git repository.

    License: Apache License 2.0

  • Flor

    Easy to use logger and automatic version controller made for data scientists who write ML code.

    License: Apache License 2.0

  • Guild AI

    Open source toolkit that automates and optimizes machine learning experiments.

    License: Apache License 2.0

  • Hangar

    Version control for tensor data, git-like semantics on numerical data with high speed and efficiency.

    License: Apache License 2.0

  • Keepsake

    Version control for machine learning.

    License: Apache License 2.0

  • lakeFS

    Repeatable, atomic and versioned data lake on top of object storage.

    License: Apache License 2.0

  • MLflow

    Open source platform to manage the ML lifecycle, including experimentation, reproducibility and deployment.

    License: Apache License 2.0

  • ModelDB

    An open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle.

    License: Unknown

    GitHub
    Website: Unknown
  • ModelStore

    An open-source Python library that allows you to version, export, and save a machine learning model to your cloud storage provider.

    License: Apache License 2.0

  • ormb

    Docker for Your ML/DL Models Based on OCI Artifacts.

    License: Apache License 2.0

  • Polyaxon

    A platform for reproducible and scalable machine learning and deep learning on kubernetes - (Video) .

    License: Apache License 2.0

  • Quilt

    Versioning, reproducibility and deployment of data and models.

    License: Apache License 2.0

  • Sacred

    Tool to help you configure, organize, log and reproduce machine learning experiments.

    License: MIT License

  • Studio

    Model management framework which minimizes the overhead involved with scheduling, running, monitoring and managing artifacts of your machine learning experiments.

    License: Apache License 2.0

  • TerminusDB

    A graph database management system that stores data like git.

    License: Apache License 2.0

Last Updated: Dec 26, 2023