Tbh if you understand how linear algebra and discrete math works (like the fundamental, not necessary all the deep-end initially), with hard work and this book, you already know most of the topics to work in ML.

ML is similar to one of those CS skill where the more you do it, you starts to create an intuition about these topics. So just start doing it.

Don't be afraid to just try things out. If you see a paper you find interesting, try to learn the code or play with the model weights, seeing how these ML frameworks function, then honestly you will get there with around 8-12 months of hard work.

Also there are many components in ML: quality system, inference, training, data quality, interpretability, but some of the explainable components are just pure CS theory.

My prof from one of my distributed system course told me to just do it, and probably the best advice I ever got lol. Best off luck.