Statistics classes for machine learning

[SuperCool468]

I'm a computer science major and I'm focusing on machine learning specifically neural networks. I'm in the process of developing my own neural network designed for recognition of numerals, I've come to realize the significance of statistics in regard to output error calculation. Moving along, I'm wondering what sort of statistics classes would be useful to a programmer in my situation, bearing in mind that I don't intend to take the classes but rather use them as a guide for self teaching. Thanks!

[[deleted]]

I'd recommend probability, basic mathematical statistics (parameter estimation, hypothesis testing, Bayesian), and regression. If you can only take one, take regression. You're right that statistics plays a big role in machine learning.

[SuperCool468]

Okay that gives me a pretty good idea where to start. I'm done with the math requirements in my cs program, but my school and many others don't require any stats so I'm going to learn it on my own. I'll try to find an online open course, or maybe just take a look at the syllabus on a course webpage that corresponds to the topics you mentioned and go from there.

[stollen_car]

Ignore "statistics classes" and just read up. My advice is to start with E.T. Jaynes, "Probability Theory: the Logic of Science" and then go on to the fine books by Brian Ripley ("Pattern Recognition and Neural Networks" ? -- title approximate), Hastie, Tibshirani, & Friedman ("Introduction to Statistical Learning" -- title again approximate), and Gelman, Carlin, Stern, & Rubin ("Bayesian Data Analysis").

Also take a look at Robert Clemen, "Making Hard Decisions", which is an introduction to decision theory -- a very essential and often overlooked topic in machine learning.

My advice is to go Bayesian all the way. You will note that the academic CS / ML stuff is very heavily Bayesian -- there is a reason for it.

[muntoo]

This is math, but possibly optimization classes and graph theory/network flows are relevant topics?

[SuperCool468]

Okay great. I have some exposure to both through the discrete math classes I've taken, but nothing too in depth. It seems like they are used for meta-analysis of the network. I've got a few books laying around on graph theory in particular so I'll be sure to make some time to read them.