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Machine Learning

1,193 items from josephmisiti/awesome-machine-learning ★74,572

tools
  1. tensorflow github.com
    tool category #python link ↗

    Computation using data flow graphs for scalable machine learning by Google.

  2. pytorch github.com
    tool category #python link ↗

    Tensors and Dynamic neural networks in Python with strong GPU acceleration.

  3. transformers github.com
    tool category #python link ↗

    State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

  4. Netron github.com
    tool category #electron link ↗

    Visualizer for deep learning and machine learning models.

  5. xgboost github.com
    tool category #python link ↗

    Scalable, Portable, and Distributed Gradient Boosting.

  6. dash github.com
    tool category #python link ↗

    Flask, JS, and CSS boilerplate for interactive, web-based visualization apps in Python.

  7. bokeh github.com
    tool category #python link ↗

    Interactive Web Plotting for Python.

  8. ray github.com
    tool category #python link ↗

    A fast and simple framework for building and running distributed applications.

  9. catboost github.com
    tool category #python link ↗

    An open-source gradient boosting on decision trees library.

  10. Bayesian Methods for Hackers github.com
    tool category #machine-learning link ↗

    by Cameron Davidson-Pilon. Introduction to Bayesian methods and probabilistic graphical models using tensorflow-probability (and, alternatively PyMC2/3).

  11. scikit-image github.com
    tool category #python link ↗

    Image Processing SciKit (Toolbox for SciPy).

  12. Opik github.com
    tool category #machine-learning link ↗

    An open-source platform for tracing, evaluating, and monitoring LLM applications. #opensource

  13. LightGBM github.com
    tool category #python-data-science link ↗

    A fast, distributed, high-performance gradient boosting.

  14. ML Workspace github.com
    tool category #machine-learning link ↗

    All-in-one web IDE for machine learning and data science. Combines Tensorflow, Jupyter, VS Code, Tensorboard, and many other tools/libraries into one Docker image.

  15. Catalyst github.com
    tool category #python-data-science link ↗

    High-level utils for PyTorch DL & RL research.

  16. m2cgen github.com
    tool category #flutter link ↗

    A CLI tool to transpile trained classic machine learning models into a native Rust code with zero dependencies.

  17. Superset github.com
    tool category #machine-learning link ↗

    A modern, enterprise-ready business intelligence web application.

  18. OpenCV github.com
    tool category #python-data-science link ↗

    Open Source Computer Vision Library.

  19. ultralytics github.com
    tool category #python link ↗
  20. streamlit github.com
    tool category #python link ↗
  21. Apache Spark (⭐44k) github.com
    tool category #integration link ↗

    Unified analytics engine whose Structured Streaming API provides scalable, fault-tolerant stream processing on the Spark SQL engine.

  22. gradio github.com
    tool category #python link ↗

    Create UIs for your machine learning model in Python in 3 minutes.

  23. pymc github.com
    tool category #python link ↗

    Bayesian Stochastic Modelling in Python.

  24. Colossal-AI github.com
    tool category #machine-learning link ↗
  25. TFLearn github.com
    tool category #python-data-science link ↗

    Deep learning library featuring a higher-level API for TensorFlow.

  26. JAX github.com
    tool category #python-data-science link ↗

    Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.

  27. Caffe github.com
    tool category #python-data-science link ↗

    A fast open framework for deep learning.

  28. Brain.js github.com
    tool category #javascript link ↗

    Neural networks in JavaScript.

  29. donnemartin/data-science-ipython-notebooks :fire::fire::fire::fire::fire: github.com
    tool category #aws link ↗
  30. huggingface/candle github.com
    tool category #rust link ↗

    [candle-core] - a minimalist ML framework with a focus on easiness of use and on performance (including GPU support)

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