Probability, Random Variables, and Stochastic Processes

I am reading this to sharpen the mathematical side of machine learning again from first principles.

The parts I care about most are:

• random variables and expectations
• conditioning and estimation
• stochastic processes that show up in signals, learning, and inference

This is the kind of book I expect to revisit repeatedly rather than read once and shelve.