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Introduction to JAX and Deep Learning

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.

Intermediate

53 Lessons

2h 30min

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Project

95 Playgrounds

14 Challenges

7 Quizzes

Course Overview

What You'll Learn

Course Content

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

TAKEAWAY SKILLS

Random Variables

Neural Networks

Functional Programming

Deep learning basics

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