Discover the power of JAX in deep learning. Gain insights into its ecosystem and learn about linear algebra, pseudo-random number generation, and optimization algorithms for cleaner, structured coding.

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JuPyter

JAX is a Python library designed for high-performance ML research. It is a powerful numerical computing library, just like Numpy, but with some key improvements.

In this course, you will learn all about JAX and its ecosystem of libraries (Haiku, Jraph, Chex, Flax, Optax). Addressing a wide range of audiences, you will cover several topics including linear algebra, random variables theory, pseudo-random number generation, and optimization algorithms.

By the end of this course, you will have a new set of skills that will make deep learning programming more intuitive, structured, and clean.

Introduction to JAX and Deep Learning

Which of these libraries is not a part of the JAX ecosystem?

Which of these libraries is not a part of the JAX ecosystem?

Which of the following is not a **side-effect**?

Which of the following is not a side-effect?

Symbolic differentiation leads to inefficient code.

Auto differentiation avoids numerical computations.

Autodiff enables us to use both forward and reverse accumulation modes.

Auto differentiation is faster at calculating the partial derivatives.

Which of the following options is not a valid reason for using the auto differentiation?

Which of the following options is not a valid reason for using the auto differentiation?

JAX doesn’t work on Python built-in structures like `tuple` or `list`

We cannot convert a `list` or `tuple` into JAX array (using `jnp.array()`)

Which of the following statements is not a difference between JAX and NumPy arrays?

Which of the following statements is not a difference between JAX and NumPy arrays?

XLA is a ______-specific compiler

Apart from the `@jit` decorator, how can we run a function using JIT?

Apart from the <code>@jit</code> decorator, how can we run a function using JIT?

It’s not advisable to use JIT execution for _______.

It’s not advisable to use JIT execution for _______.

Test your knowledge of the JAX programming model by completing this quiz.

Introduction

JAX Programming Model

Linear Algebra

Random Variables and Distributions

JAX Ecosystem

Project: GAN Using the JAX ecosystem

Appendix

Quiz: Basics of JAX