[hiram112]

How much machine learning have you been able to pick up and did you learn formally (in school) or just on your own? It's a broad subject, so where would you recommend one begin, assuming I have a decent undergrad math background? Thanks!

[pbhjpbhj]

Not the parent, but I did an undergrad maths/physics degree some time back and found https://www.coursera.org/learn/machine-learning to be good as an introduction, unfortunately a new job [unrelated] has prevented my finishing the course but I hope to pick it up again later in the Winter.

I would be interested in thoughts from anyone with ML experience who has reviewed said course's materials?

[Enginerrrd]

I've always had way too much math under my belt which helps a lot and have taught myself a lot of genuine computer science out of personal interest. I actually did Andrew Ng's Coursera machine learning class all the way through as a first introduction to that field before realizing it wasn't so mysterious and was just the application of a lot of math I already knew, then ran through a bunch of tensor flow tutorials when that first came out and the like. Then just experimented on my own. I have a knack for data though.

Formally from school, I've only had 3 semesters of scientific programming in Fortran and a shitload of math. That and years and years of building models and massaging data in Excel.

Mostly I'm just really used to learning a new API/tool and applying it to new things.

A lot of the ML stuff hasn't been fancy ML, just basic things but applied in really clever and novel ways.

[codesushi42]

Study stats and convex optimization. If you understand logistic regression and MLE, you're mostly there.