I am a microbiologist and I am currently self-studying machine learning from some open lecture videos. I am finding it pretty difficult to understand proofs that are somewhat "obvious", my poor mathematical knowledge is to blame for that. Can you please recommend a text-book that deals with the mathematical proofs of the theorems? Or approaches machine learning from the mathematical side?
MOOC Course on Machine Learning: https://www.coursera.org/course/ml
Guide to Mathematical Proofs from berkeley: https://math.berkeley.edu/~hutching/teach/proofs.pdf
This might be helpful:
Machine Learning by Tom Mitchell
According to the Centre for Computational Statistics and Machine Learning:
"A good introduction book for machine learning in general. It is easy to read and goes at a low pace. Some topics are a bit dated and not very popular currently and some of the recent progress as kernel methods and graphical models are missing. But it includes an overview to genetic algorithms and reinforcement learning. I suggest to read chapters 1, 4-9 and 13."