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aymericdamien/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
A collection of TensorFlow examples covering everything from linear regression to GANs, maintained in both TF v1 and v2 variants. It's aimed at people learning TensorFlow who want working code to read alongside the official docs. With 43k stars it's one of the most-forked ML tutorial repos on GitHub.
The side-by-side approach of showing the same model in both raw TF and the high-level Keras API is genuinely useful — you see what the abstraction is hiding. Both notebook and plain .py versions exist, so you're not forced into Jupyter. Coverage is broad without being shallow: data pipelines, TFRecords, multi-GPU training, and TensorBoard are all there, not just MNIST classifiers. The v1/v2 split is clean rather than a messy compatibility shim.
Last substantive update was 2020; the TF2 section is noticeably thinner than v1 (no VAE, no GAN, missing several models), which suggests the migration stalled halfway. Nothing here touches transformers, JAX-style functional patterns, or tf.data's more recent features — if you're learning TensorFlow in 2025 you'll hit the edges of this repo fast. The examples all use MNIST or toy datasets, so there's no guidance on handling real-world data scale or production training loops. No requirements.txt or environment file means 'just pip install tensorflow' is the entire setup story.