Introduction to JAX and Deep Learning
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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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Course Overview

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 sk...Show More

JAX is a Python library designed for high-performance ML research. It is a powerful numerical computing library, just like Numpy...Show More

WHAT YOU'LL LEARN

Learn the basics of JAX

Learn how to apply Autograd

Use auto vectorization for batching

Use Haiku and Flax for implementing neural networks

Cover Optax and overview of common optimization algorithms in deep learning

Use Chex for testing JAX programs

Learn the basics of applied linear algebra

Learn random variables theory and probability distributions

Learn pseudo-random number generation

Cover the basics of optimal transport