Machine Learning on the Cheap and Easy

http://thunderboltlabs.com/posts/machine-learning-on-the-cheap-and-easy

110 15 15 years ago

colincsl• 15 years ago

Thanks for the link!

Not to try to highjack the post, but for those interested in resources for computer vision see my post from a few months ago: http://colinlea.posterous.com/on-self-guided-study-of-comput...

evilmartini4• 15 years ago

Good stuff - I added http://szeliski.org/Book/ to my reading list, thanks for sharing the link. There's a huge overlap for certain classes of problems. CV in many ways resembles the same problems with large online data streams, noisy, time critical, huge volumes of data - feature extraction is problematic. Hybrid solutions usually required.

I've found that reading books from other ML domains helps out in understanding the application and getting ideas on how to approach the problem.

nphrk2• 15 years ago

As I experienced it, Szeliski's book is better as a reference as it covers lots of material (just see the number of citations at the end). I don't think it's an easy read without reading (some of) the cited papers (or having background knowledge).

raffi• 15 years ago

For getting started I really liked Toby Segarin's Programming Collective Intelligence. It was my introduction to this area before I went on to produce After the Deadline.

evilmartini4• 15 years ago

I read that one, I liked the fact that he builds up each example from first principles. It's hard to find explanations that bridge theory and practice.

runciter2• 15 years ago

this is like recipes for doing machine learning, not deep enough.

Fivesheep• 15 years ago

I think the two free online courses provided by Stanford last year is really good for beginners.

teeray• 15 years ago

It's also one of the courses complete with materials in the new iTunes U app.

binarysolo• 15 years ago

Thanks for the head's up... been meaning to watch it as a refresher.

evilmartini4• 15 years ago

I found the Stanford course almost assumed too much of a stats background to make it easily accessible. Starting with the math foundations is sound, but scary for people who don't dream in LaTeX :)

pm90• 15 years ago

also, an HN'er posted his notes on Andrew Ng's class on ML...I learnt more from this than from the videos, as the videos take much too long.

link: http://holehouse.org/mlclass/

3pt14159• 15 years ago

These are really, really basic tools and books. Once you're past this you can get a copy of some good Springer books (e.g. "Recommender Systems Handbook") and follow up on the papers and studies referenced.

nphrk2• 15 years ago

I woundn't consider The Elements of Statistical Learning Theory a (very) basic book. It covers plenty of material in relatively good depth.

runciter2• 15 years ago

I highly recommend the 'elements of statistical learning' but also Bishop's 'pattern recognition and machine learning'

evilmartini4• 15 years ago

I just added it to my list of books to review. Thanks for mentioning it. What did you like about Bishop's Book?

Machine Learning on the Cheap and Easy

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