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Data Version Control - Git for Data & Models - ML Experiments Management.
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Python library for experiment metrics logging into simply formatted local files.
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Scala Library/REPL for Machine Learning Research.
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An evolutionary optimization library.
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Deep learning operations reinvented (for pytorch, tensorflow, jax and others).
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Python package which helps to debug machine learning classifiers and explain their predictions.
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A simple and functional machine learning library written in Elixir.
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A library that builds, optimizes, and evaluates ML pipelines using domain-specific functions.
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Interactive reports to analyze ML models during validation or production monitoring.
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Face recognition library that recognizes and manipulates faces from Python or from the command line.
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Foundational Models for State-of-the-Art Speech and Text Translation.
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Visualizations for understanding and analyzing machine learning datasets.
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Industrial Grade Federated Learning Framework.
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Feature store for machine learning.
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Feature engineering package with SKlearn like functionality.
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Set of tools for creating and testing machine learning features, with a scikit-learn compatible API.
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Python library for automated feature engineering.
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A highly-modular C++ machine learning library for embedded electronics and robotics.
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Secure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
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PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
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Dynamic Tensor Graph library in Clojure (think PyTorch, DynNet, etc.).
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Easy-to-use and flexible AutoML library for Python.
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This basically to gauge the understanding of Machine Learning Workflow and Regression technique in specific.
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Friendly Federated Learning Framework.