GitHub's deep learning leaderboard, cryogenically frozen in July 2020

What it does This repository is a single curated markdown table of popular deep learning projects on GitHub, sorted strictly by star count. It aggregates frameworks, libraries, tutorials, and research tools—from TensorFlow and PyTorch to face_recognition and DeepFaceLab—into one skimmable leaderboard. It is essentially glue code, kindly assembled: no algorithms, just an index.

The interesting bit The list is an accidental time capsule of the deep learning zeitgeist circa July 2020. Seeing transformers at 30.4k stars and PyTorch at 40k captures the hierarchy just before the modern large-language-model explosion made those numbers look quaint.

Key highlights

• Ranks projects purely by GitHub stars, making relative popularity immediately visible
• Mixes frameworks, application libraries, tutorials, and datasets in one table
• Includes unexpected entries alongside the obvious giants
• Provides one-line descriptions for quick scanning

Caveats

• Last updated July 2020; star counts and project relevance are now severely stale
• Some entries (e.g., julia, awesome-scalability) stretch the definition of “deep learning project”

Verdict A fun archaeological dig for anyone curious what the DL landscape looked like in mid-2020, but useless as a current discovery tool. Researchers and engineers should find a maintained awesome-list instead.