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Understanding Machine Learning: From Theory to Algorithms [pdf] (huji.ac.il)
24 points by mindcrime on Jan 26, 2016 | hide | past | favorite | 6 comments



This looks interesting, but the first page literally says not to post the link to the PDF, but post to here instead: http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning....


The thing is, I read that, and totally mis read it. I was thinking the author meant to say "don't post a copy of this PDF to your own server and link to it". It never occurred to me that he meant "don't link to this PDF". (I glanced at the URL there and saw that the domain part was the same, and assumed that the link was the PDF link).

Oh well, if an admin sees this and wants to change the link, that would be cool. If not, well... what can ya do?


Has someone used this book? I am currently doing Abu-Mostafa's Caltech course (Link for the interested: https://work.caltech.edu/telecourse.html) and I would like to know if it is a good complement.


I haven't, I just discovered this book and thought it looked useful. The book I have been getting some mileage out of, even though it's a bit dated, is Fundamentals of Neural Networks: Architectures, Algorithms And Applications by Laurene Fausett.

https://www.amazon.com/gp/product/0133341860/ref=oh_aui_deta...

I've also been looking at Neural Network Design by Martin Hagan.

https://www.amazon.com/gp/product/0971732116/ref=oh_aui_deta...

That one is also freely available online:

http://hagan.okstate.edu/nnd.html


NN != Statistical machine learning


Fair enough, but the LfD class that @cuchoi mentioned does include a section on NN. And there are common principles, like understanding the variance/bias tradeoff, etc., that are common across many different ML approaches.




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