[why-el]

So I was wondering if any fellow HNer is on a quest to be at least comfortable around these problems. Can you share your plans? Currently I am starting with some linear algebra and I have plans to move to statistics then pick up a book on machine learning. I would really use some advice.

[achompas]

I'm on this path right now. Working simultaneously on a MSCS at NYU and a full-time developer gig at Knewton (a company which truly understands the value and risks of data R&D).

I'd really start with this awesome curriculum[0] by Joseph Misti. He nails the mix of modeling, algorithms, math/stats, development, and distributed/Unix skills one needs to become comfortable around these problems. More importantly, his advice agrees with my experience on the data team at Knewton--we really use a bit of all of the above skills to solve our problems.

My email is in my profile if you (or anyone else) would like to chat about this a bit more. I'm also in NYC, and totally willing to grab tea and chat in person.

[0] http://www.quora.com/What-skills-are-needed-for-machine-lear...

[seanharnett]

Andrew Ng's machine learning class on coursera is a very nice, easy introduction to the subject.

[why-el]

Yes, and I started that before realizing that I need more background knowledge, hence starting with some math. :)