Machine Learning books

[WhatARoaster]

Hey guys,

 

Just looking to see if any one has any suggestions for good books on machine learning?

Cheers

[Flojer0]

I haven't read any books yet, but coursera has a class on machine learning that has been doing really well at making me feel comfortable enough to actually learn and get stuff done. The current class is already happening and nearly over. But I would recommend keeping an eye out for then the class runs again.

 

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

[WanderingFool]

Anything in particular that you want to learn from machine learning...there are multiple ways of approaching the problem, and some of them can get very mathematical (dealing with probabilities, and bet fits of curves).

 

Also what depth would you like. (Personally I only have experience in neural networks, and only heard of the others)

[WhatARoaster]

Anything in particular that you want to learn from machine learning...there are multiple ways of approaching the problem, and some of them can get very mathematical (dealing with probabilities, and bet fits of curves).

 

Also what depth would you like. (Personally I only have experience in neural networks, and only heard of the others)

 

Honestly im just looking for a solid overview book, nothing that focuses on a specific area too greatly.

 

Let's just say im in my masters year of a CIS & EEE degree, none of the classes ive picked in uni really have covered machine learning, hence why i just want a good overview and im not really worried about how in depth it may get.

[Darkfeign]

I'm a PhD student at Bristol and part of the ISL group whose population is about 70% machine learners so, while I don't have anyone on hand to ask, the lecturer who leads the machine learning module recommends the following books:
 

Duda, Hart, Stork, "Pattern Classification", Wiley, 2000

 

Hastie, Tibshirani, Friedman, "The Elements of Statistical Learning", Springer, 2001.

 

Shawe-Taylor, Cristianini, "Kernel Methods for Pattern Analysis", Cambridge University Press, 2004. (Christianini is a Bristol professor whose work covers a lot of Computational Genomics from his module also, which uses machine learning with biology if you're interested. His additional book is titled: "Introduction to Computational Genomics: A Case Studies Approach")

Another possible one that is not machine learning specific, but maths related to probability and uncertainty is:
The uncertain reasoner's companion, - a mathematical perspective, Jeff Paris, Cambridge Tracts in Theoretical Computer Science.

I've been working through this one and it's been quite valuable given my lack of a mathematical background. Hope this helps.

[Cheesebaron]

There is also a lot of useful things to gather from the NLTK book even though it might not be the language you are using for Machine Learning it still goes through a lot of stuff about the topic.