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https://github.com/ritchieng/the-incredible-tensorflow

The Incredible TensorFlow 2: a curated list of tutorials, papers, projects, communities and more relating to TensorFlow 2.
https://github.com/ritchieng/the-incredible-tensorflow

tensorflow tensorflow-models tensorflow-tutorials tensorflow2

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The Incredible TensorFlow 2: a curated list of tutorials, papers, projects, communities and more relating to TensorFlow 2.

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# The Incredible TensorFlow 2

This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the TensorFlow 2. Feel free to make a pull request to contribute to this list.

## Tutorials
- [TensorFlow 2.0 Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)
- [Overview](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/01-TF2.0-Overview)
- [Static vs Dynamic Graph](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/02-AutoGraph)
- [FNN with MNIST](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/03-Play-with-MNIST)
- [Linear Regression](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/04-Linear-Regression)
- [FNN with FashionMNIST](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/05-FashionMNIST)
- [VGG with CIFAR](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/06-CIFAR-VGG)
- [Inception with MNIST](https://github.com/dragen1860/TensorFlow-2.x-Tutorials/tree/master/07-Inception)

## CNNs
- [YoloV3](https://github.com/zzh8829/yolov3-tf2)

## GANs, VAEs, and AEs
- [CycleGAN: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://github.com/LynnHo/CycleGAN-Tensorflow-2)
- [Music Transformer: Generating Music with Long-Term Structure](https://github.com/jason9693/MusicTransformer-tensorflow2.0)
- [CartoonGAN: CartoonGAN: Generative Adversarial Networks for Photo Cartoonization](https://github.com/mnicnc404/CartoonGan-tensorflow)

## NLP
- [HuggingFace Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0](https://github.com/huggingface/transformers)

## Interpretability
- [Model Interpretability Introduction](https://colab.research.google.com/drive/1xM6UZ9OdpGDnHBljZ0RglHV_kBrZ4e-9)

## Credits
This is based off my more long-standing established repository [The Incredible PyTorch](https://github.com/ritchieng/the-incredible-pytorch).

## Contributions
Do feel free to contribute!

You can raise an issue or submit a pull request, whichever is more convenient for you. The guideline is simple: just follow the format of the previous bullet point. **Take note, implementations are strictly based on TensorFlow 2 onwards only.**