This may be of interest to some-

One of the authors of Learning from Data, Hsuan-Tien Lin, just started a Coursera course on Machine Learning taught in Mandarin Chinese (with English slides).

https://www.coursera.org/course/ntumlone

One thing I really like about Learning from Data is that it gives Machine Learning a certain "framework" instead of just being a hodgepodge of different techniques. The book is quite clear on the mathematical underpinnings, while at the same time introducing various "rules of thumb" for practical considerations.

Extensive previous discussion:

https://news.ycombinator.com/item?id=4206445

Excellent - thank you - upvoted!

That discussion is now closed, of course, and is more than 18 months old. It would be interesting and useful to see if anyone has an update about their use of the material.

Looking forward to see if anyone has anything to add.

Edit: Especially love the link to Hilary Mason's "Everything you need to know about Machine Learning in 30 minutes or less".[1]

[1] www.hilarymason.com/presentations-2/devs-love-bacon-everything-you-need-to-know-about-machine-learning-in-30-minutes-or-less/

that's more than a year ago... thanks for surfacing it up.

Thanks for the link! I am taking Andrew Ng's Coursera class now - homework due today. I am finding it to be a good introductory class. I think probably equivalent to an introductory undergraduate class. This is perfect for me because my formal calculus and statistics skills have a atrophied in the 10 years since I took those classes in college. The pace is enough to push be to get back into math shape and learn some base algorithms used in ML applications. I have bookmarked this for follow up since I have a practical need to get deeper into ML.

Yaser is giving an edX course now: https://www.edx.org/course/caltechx/caltechx-cs1156x-learnin...