[D] How to organize deep learning projects on Github ?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

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  • lightning-bolts

    Toolbox of models, callbacks, and datasets for AI/ML researchers.

  • Also PyTorch Lighting gives example in this repo https://github.com/PyTorchLightning/pytorch-lightning-bolts

  • detectron2

    Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

  • You can check these repos: https://github.com/open-mmlab/mmdetection https://github.com/facebookresearch/detectron2

  • InfluxDB

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  • cookiecutter-pytorch

    A Cookiecutter template for PyTorch Deep Learning projects.

  • I use this cookie cutter https://github.com/khornlund/cookiecutter-pytorch

  • Kedro

    Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

  • Check Kedro (https://github.com/quantumblacklabs/kedro) they provide a project structure that looks like extended and a little bit improved CookieCutter + Kedro pipelines of course.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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