This repository is a curated list of popular deep learning projects on GitHub, ranked by stars, last updated in July 2020. It serves as a valuable resource for developers, researchers, and students looking to explore influential tools and frameworks in the deep learning landscape. The list provides a quick overview of key projects, their star counts, and brief descriptions, enabling users to identify trending and widely adopted technologies.

How It Works

The repository functions as a static snapshot of GitHub's deep learning ecosystem, compiled by manually aggregating and ranking projects based on their popularity (measured by GitHub stars). This approach offers a straightforward, albeit time-sensitive, view of the community's focus and the impact of various deep learning libraries and applications.

Quick Start & Requirements

This repository is a list and does not require installation or execution. It serves as a reference guide.

Highlighted Details

• Features projects like TensorFlow (146k stars), Keras (48.9k stars), OpenCV (46.1k stars), and PyTorch (40k stars).
• Includes a wide range of categories such as computer vision, natural language processing, and general machine learning frameworks.
• Highlights projects focused on specific applications like face recognition, deepfakes, and OCR.

Maintenance & Community

The repository's last update was July 9, 2020. It is a static list and does not appear to have active maintenance or community engagement features.

Licensing & Compatibility

The licensing of individual projects listed is not specified. This repository itself does not have a license as it is a curated list.

Limitations & Caveats

The data is outdated as of July 2020, meaning it does not reflect the current state or popularity of deep learning projects. The ranking is solely based on star count, which may not always correlate with a project's technical merit or suitability for specific use cases.