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O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

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Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#31

Post by ralphc »

silentbicycle wrote: post #11
codypo wrote: post #9

The Programming Collective Intelligence book on sale here is wonderful! If you want to build software that does something intelligent thanks to the mining of a tremendous set of data (think recommendation engine, price models, content classification, search engine, etc) and you're not sure where to start, start with this book. Not being a CS academic, it's hard to find useful, non-trivial introductions that I can und…

Seconded. It's got some minor errors* and omissions, but after reading it for the concepts, I've found other data mining / machine learning books much easier to follow. The explanations are usually pretty good. * I've been doing the exercises in Lua, and got stuck on one of them - the listed algorithm (IIRC) erroneously ended with "1 - num/denom" rather than "num/denom". It's listed correctly earlier. (I can look up…

Off and on I've been doing the exercises and examples in Clojure, and it's a little difficult because the Python examples seem so imperative to me. It's been a challenge turning them into functional code, there's a couple of places where I go over a list twice when I probably should be able to get all I need with one pass, and of course when I have to resort to using an atom or ref I feel a little dirty.

Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#32

Post by [deleted] »

ralphc wrote: post #31
silentbicycle wrote: post #11

Earlier quoted context omitted.

Seconded. It's got some minor errors* and omissions, but after reading it for the concepts, I've found other data mining / machine learning books much easier to follow. The explanations are usually pretty good. * I've been doing the exercises in Lua, and got stuck on one of them - the listed algorithm (IIRC) erroneously ended with "1 - num/denom" rather than "num/denom". It's listed correctly earlier. (I can look up…

Off and on I've been doing the exercises and examples in Clojure, and it's a little difficult because the Python examples seem so imperative to me. It's been a challenge turning them into functional code, there's a couple of places where I go over a list twice when I probably should be able to get all I need with one pass, and of course when I have to resort to using an atom or ref I feel a little dirty.

[deleted]

Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#33

Post by rachelj »

3pt14159 wrote: post #7

Has anyone read "Data Analysis with Open Source Tools"? http://oreilly.com/catalog/9780596802356/ I can't seem to look through the book, not even at Amazon, which I like to do before buying something.

The table of contents is now available on the book's catalog page (http://oreilly.com/catalog/9780596802356/), and you can view the table of contents and preview snippets of the content on Safari (http://my.safaribooksonline.com/9781449389802?portal=oreilly...).

Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#35

Post by Homunculiheaded »

Goosey wrote: post #18
askedrelic wrote: post #17

Earlier quoted context omitted.

Ebooks :( For personal use, this would be fine, but it's much easier to share paper books at work.

I find that I simply can't use ebooks. Sitting and reading on a computer monitor for long periods of time is just too much strain on my eyes. Funny enough that I don't have as much issue coding all day or reading hackernews.. but if I sit and try to read multi-page articles or ebooks it just seems impossible to do if it isn't on paper. This is the one thing that tempts me into a Kindle. I wouldn't want to replace my…

I have the smaller kindle and I've been pleasantly surprised by the number of technical ebooks that read nicely on it (they have to be .mobi though as pdf are not nearly as pleasant). I've also found that I now prefer ebooks on my laptop for any exercise heavy reading. For example right now I have half my screen devoted to emacs+slime and the other have to 'land of lisp', I've found this much better than trying to balance a print book and a laptop. I still need/prefer print books in certain situations, but I'm happy with the shelf space this saves. Also don't forget that you permanently have multi-format, drm-free access to O'Reilly ebooks.

Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#36

Post by jzawodn »

toby wrote: post #21
codypo wrote: post #9

The Programming Collective Intelligence book on sale here is wonderful! If you want to build software that does something intelligent thanks to the mining of a tremendous set of data (think recommendation engine, price models, content classification, search engine, etc) and you're not sure where to start, start with this book. Not being a CS academic, it's hard to find useful, non-trivial introductions that I can und…

Thanks! I'm the author of this book, and it always makes me so happy whenever I read a comment like this on HN :)

I hate to "met too" but I'm a big fan of it as well! I've built a few of the python examples into their perl equivalents over the last few months. Someday I should throw 'em up on github.

Re: O'Reilly discounts: machine learning, nltk, hadoop, sql, nosql, aws and appeng

#37

Post by kranner »

codypo wrote: post #9

The Programming Collective Intelligence book on sale here is wonderful! If you want to build software that does something intelligent thanks to the mining of a tremendous set of data (think recommendation engine, price models, content classification, search engine, etc) and you're not sure where to start, start with this book. Not being a CS academic, it's hard to find useful, non-trivial introductions that I can und…

I'd like to add that Stephen Marsland's 'Machine Learning: An Algorithmic Perspective' is a new book in the same practical/introductory class. The code is mostly numpy.

http://www-ist.massey.ac.nz/smarsland/MLbook.html

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