Episode 19

Is Julia Better Than JAX For Machine Learning?


May 16th, 2022

48 mins 22 secs

Your Hosts

About this Episode

David and Randy respond to an article that makes the case for JAX over Julia for machine learning, particularly when applied to solving differential equations.

David also shares a series of workshops hosted by the Julia Gender Inclusive community, as well as a new package by Elias Carvalho for creating truth tables from Julia expressions, and Randy explores a YouTube series and set of Pluto notebooks all about partially observable Markov processes.

Support Talk Julia on Ko-Fi

We're excited to announce that we have opened up podcast memberships! Become a member for as little as $5/mo to get early access to episodes, social media shoutouts, and, starting at $10/mo and up, access to a members-only "office hours" call.

Your support helps us continue to bring you interviews and educational Julia content each week. It also helps us grow sustainably and improve the quality of the podcast.

Become a member today 👉

Manning Publications Discount

We've partnered with Manning Publications to bring all of our listeners a special 35% discount code on all of Mannings physical books, ebooks, courses, and more. There's no expiration date and you can use the discount as many times as you like!

Just visit http://mng.bz/pOzw and use the code podtalkjulia22 at checkout to get 35% off of your order!

Episode Links