tensorflow/tensorflow
An Open Source Machine Learning Framework for Everyone
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
1 release in the last 90 days, the latest 42 days ago, with 414 contributors on GitHub.
Gained 143% more stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides an end-to-end open source platform for machine learning with tools, libraries, and community resources.
- Offers a comprehensive and flexible ecosystem supporting multiple languages and hardware accelerators for scalable ML development.
- Use for developing and deploying deep learning models with Python and C++ APIs on GPUs and CPUs.
- Use for conducting machine learning research and experimentation with state-of-the-art neural network architectures.
- Use for integrating ML-powered features into applications across platforms including Linux, Windows, macOS, Android, and embedded devices.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the framework is versatile enough to be used in other areas as well.
TensorFlow provides stable Python and C++ APIs, as well as a non-guaranteed backward compatible API for other languages.
Keep up-to-date with release announcements and security updates by subscribing to [email protected]. See all the mailing lists.
See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+4,334 stars over 80 days across 9 snapshot days; best day +153 on Sep 27.
Forks
78.2K+2.2K
Open issues
3.5K+586
Compared with peers in Deep Learning
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| rohitg00/ai-engineering-from-scratch | 78.3K | +1.6K | 75 | 1 day ago |
| tensorflow/tensorflow | 201.3K | — | 63 | 42 days ago |
| SYSTRAN/faster-whisper | 26.5K | — | 40 | 368 days ago |
| GeeeekExplorer/nano-vllm | 16.3K | — | 12 | — |
| Lightning-AI/litgpt | 13.8K | — | 58 | 129 days ago |
| data-privacy-stack/presidio | 11.8K | — | 64 | 10 days ago |
| Category median | 16.3K | — | 58 | — |
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