How to study mathematics for Data Mining, Machine Learning, etc.?

Question

Mathematics

Hello.
I studied engineering, and there was no discrete mathematics at all (except for the basics of probability theory). Six months ago I decided to become a programmer, because before that it was just a hobby. Somehow, for the sake of interest, I took a course on machine learning on coursera. I don’t even know how to describe what feelings overwhelmed me when I passed the first week) In general, I firmly decided that this is what I want to do. However, I realized that my mathematical preparation is clearly weak.
I want to ask people who work/study in similar areas for advice on what and in what sequence it is better to learn in order to raise their level.
The question is, of course, extremely abstract, but I hope someone will share their opinion, recommend literature.
The first thing I realized would be nice to learn statistics - I started with it.
Next, I plan to tighten the terver and combinatorics. Is it correct?

Answer 1

Start with probability theory, go through combinatorics along the way. Then statistics.
In parallel - look into functional analysis and linear algebra.
You can immediately start reading something like Murphy or Bishop on machine learning to make it more fun.
ps if you are a gourmet, add general algebra for dessert :).

Answer 2

Throw in some linear algebra and some math.

Answer 3

on edx.org:
MITx 6.041x Introduction to Probability - The Science of Uncertainty Course Starts - Feb 04, 2014
UTAustinX UT.5.01x LAFF: Linear Algebra - Foundations to Frontiers Course Starts - Jan 16, 2014

Answer 4

I forgot to add - I never had any problems with mathematics, and even now I remember a lot of what I went through. So you can advise and something more complicated.