Books every machine learning engineer should read

Just a quick announcement of a resource addition to the ML for SWEs repo

I’ve put together a list of books containing the knowledge every machine learning engineer should have. This list is kept lean on purpose to give you everything you need without wasting your time. It includes books on:

> ML math

> Core ML algorithms and concepts

> System design

> Machine learning system design

> Building with popular ML tools and frameworks

> Interview prepration

Check out the whole thing at the Machine Learner’s Library inside the ML for SWEs repo.

This is also a reminder about the ML for SWEs repo that will be updated regularly with learning resources and hands-on code examples. Don’t forget to star it! 🌟

If this resource is missing anything or you disagree with some of the choices, let me know in the comments.

If you’re not a member of ML for SWEs and you want to resources and ML lessons in your inbox each week, don’t forget to subscribe.

Always be (machine) learning,

Logan