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+# "Deep Learning with JAX" book
+
+This is a repository accompanying the "[Deep Learning with JAX](https://www.manning.com/books/deep-learning-with-jax)" book (originally called "JAX in Action"). Feel free to use the promotional code **au35sap** for 35% discount for this book and any other Manning's product.
+
+[![Deep Learning with JAX](Sapunov-MEAP-HI.png)](https://www.manning.com/books/deep-learning-with-jax)
+
+Notebooks for the chapters:
+1. [Intro to JAX](Chapter-1)
+   - [JAX Speedup](Chapter-1/JAX_in_Action_Chapter_1_JAX_speedup.ipynb)
+2. [Your first program in JAX](Chapter-2)
+   - [MNIST image classification with MLP in pure JAX](Chapter-2/JAX_in_Action_Chapter_2_MNIST_MLP_Pure_JAX.ipynb)
+3. [Working with tensors](Chapter-3)
+   - [Image Processing with Tensors](Chapter-3/JAX_in_Action_Chapter_3_Image_Processing.ipynb)
+   - [Working with DeviceArray's](Chapter-3/JAX_in_Action_Chapter_3_DeviceArray.ipynb)
+4. [Autodiff](Chapter-4)
+   - [Different ways of getting derivatives](Chapter-4/JAX_in_Action_Chapter_4_Different_ways_of_getting_derivatives.ipynb)
+   - [Working with gradients in TensorFlow, PyTorch, and JAX](Chapter-4/JAX_in_Action_Chapter_4_Gradients_in_TensorFlow_PyTorch_JAX.ipynb)
+   - [Differentiating in JAX](Chapter-4/JAX_in_Action_Chapter_4_Differentiating_in_JAX.ipynb)
+5. [Compiling your code](Chapter-5)
+   - [JIT compilation and more: JIT, Jaxpr, XLA, AOT](Chapter-5/JAX_in_Action_Chapter_5_JIT.ipynb)
+6. [Vectorizing your code](Chapter-6)
+   - [Different ways to vectorize a function, Controlling vmap() behavior, More real-life cases](Chapter-6/JAX_in_Action_Chapter_6_vmap.ipynb)
+7. [Parallelizing your computations](Chapter-7)
+8. more to come
+
+TBD
+
+Google ML Developer Programs team supported this work by providing Google Cloud Credit