For much simpler content on Machine Learning/Data Science stuff with Python.

For Python programming generally, inc. how to start it up and make it run code and best practices etc. the Crash Course book is good.

Quite a good foundational textbook for Machine Learning, not quite as hands-on as Aurelien Geron though.

I wrote this book :) Basically the Machine Learning tools are the same, except in this book I deliberately set out at the beginning to make it pick stock for you that you might invest in.

This book is closer to what one might consider a complete book about machine learning.

Damon Lee uses Machine Learning algorithms from a popular Python framework called Scikit-Learn. By far the best book on using this library for general Machine Learning usage is "Hands On Machine Learning"

For a book that has like 10X the content (but you'll probably need 10X the time to read it all). This is probably the best Python Machine Learning book right now. It covers everything up to GPU stuff, whereas Data Science From Scratch basically scratches the surface because it is starting from zero.

If you plan on using machine learning stuff then you're probably better off starting with Hands-On Machine Learning.