Honest question - I have several machine learning with Python books that I'm about to dive into but before doing so, which resources would you recommend a complete beginner in ML to read?
Then I'd do a Kaggle. I like Kaggle because the datasets are well prepared, and the problems are well stated. There are plenty of other similar datasets etc if you don't want to do that.
First, learn and understand the central limit theorem. That will force you to understand enough statistics to not be dangerous.
Then I'd work through https://www.kaggle.com/omarelgabry/titanic/a-journey-through... until I can do the whole thing myself.
Then I'd do a Kaggle. I like Kaggle because the datasets are well prepared, and the problems are well stated. There are plenty of other similar datasets etc if you don't want to do that.
I don't know any specific Python books though.
[1] https://www.khanacademy.org/math/statistics-probability/samp... maybe? I haven't watched these, but generally the Khan Academy stuff is a good place to start.