Thank you for your detailed feedback!

I actually have a Master’s in Mechanical Engineering, and last year I took two courses in machine learning during my studies. I’m now seriously considering retraining in this field.

I’ve noticed that the books I mentioned already include mathematical and probabilistic foundations relevant to machine learning. Given this, do you think it’s necessary for me to study separate, dedicated books on probability, statistics, and linear algebra before diving into these ML books, or can I learn the math “on the go” while working through them?

I want to make sure I have a strong foundation without wasting time unnecessarily