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Comment by romaniv | Hacker News Reader

There is more to AI than complicated neural networks. There are simple well-studied algorithms that deliver predictable results and work very well if you apply them to the right problem. Look into K-means clustering, linear regression and decision trees to get the taste.

Good introduction to the field: http://ocw.mit.edu/courses/electrical-engineering-and-comput...

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Agreed. Deep learning receives all the hype these days (look at the machine learning subreddit), but in reality it provides very little practical value for the vast majority of data mining tasks that most folks will see. For that, standard methods like you mentioned (and don't forget SVM of course!) are still the go-to methods in my toolbox.

On a more practical side, there is a good AI book with a misleading name: Programming Collective Intelligence. Instead of going over some abstract algorithms, it poses a series of practical questions (recommend a movie, calculate optimal price, filter spam) and then shows (with source code!) how to solve them using common AI techniques.

Appreciate the recommendation (I wrote that)! Honestly the book is very old at this point, it may still be an approachable way to understand what's behind the algorithms but there are much better ways to write the code now.

I wore out my copy. Have you come across any books or course with the same approach but more updated code to recommend?

Are you speaking about just the code samples or commenting on the general approaches used in the book?

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