YoVDO

JAX- Accelerated Machine Learning Research via Composable Function Transformations in Python

Offered By: Fields Institute via YouTube

Tags

Machine Learning Courses Python Courses JAX Courses

Course Description

Overview

Explore accelerated machine learning research through composable function transformations in Python with JAX in this 52-minute seminar presented by Matthew Johnson from Google. Delivered as part of the Machine Learning Advances and Applications Seminar series at the Fields Institute, learn how JAX can enhance and streamline your machine learning workflows, offering powerful tools for researchers and practitioners alike.

Syllabus

JAX: accelerated machine learning research via composable function transformations in Python


Taught by

Fields Institute

Related Courses

Artificial Intelligence for Robotics
Stanford University via Udacity Intro to Computer Science
University of Virginia via Udacity Design of Computer Programs
Stanford University via Udacity Web Development
Udacity Programming Languages
University of Virginia via Udacity