In addition to the above answers you may consider the book by Chris Bishop, Pattern Recognition and Machine Learning, Springer, 2007, ISBN-10: 0387310738, ISBN-13: 978-0387310732

It is considered a classic textbook on the subject.

Introduction to Machine Learning, second edition

By Ethem Alpaydin

ISBN: 9780262012430

Thanks!

You are welcome!

you can also try the course from coursera.org its really helpful.

https://www.coursera.org/course/ml 

In addition to the above answers you may consider the book by Chris Bishop, Pattern Recognition and Machine Learning, Springer, 2007, ISBN-10: 0387310738, ISBN-13: 978-0387310732

It is considered a classic textbook on the subject.

The classic is Hastie, Tibshirani, Friedman 'Elements of Statistical Learning'. You don't want to be without that -- its data sets are now int he ElemStatLearn package in R.

have a look at The Elements of Statistical Learning

If you are not limited to books, i recommend Machine Learning course of coursera's founder Andrew Ng. It has great home works and practices for  better understanding of theoretical concepts in practice. You can find it here:

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

but if you need a very structural content you can use Christopher M.Bishop "Pattern Recognition and Machine Learning" book.

ISBN-10: 0-387-31073-8

ISBN-13: 978-0387-31073-2

An Introduction to Statistical Learning with Applications in R, by James, G., Witten, D., Hastie, T., Tibshirani, R., 1st edition, Springer, 2013.

If you only had one book to study from, then make it Bishop's Pattern Recognition and Machine Learning as suggested above.

Bishop was also suggested to me for the same purpose.

Apart from the books mentioned above read this also. Data Mining: Practical Machine Learning Tools and Techniques.The third edition was published in January 2011 by Morgan Kaufmann Publishers (ISBN: 978-0-12-374856-0). Mark Hall has joined Ian Witten and Eibe Frank as co-author for this edition, which has expanded to 629 pages.

Machine Learning and Data Mining, By I Kononenko and M Kukar

https://www.elsevier.com/books/machine-learning-and-data-mining/kononenko/978-1-904275-21-3

One good reference is 

Machine Learning

The Art and Science of Algorithms that Make Sense of Data 

From Peter Flach  

Gives the foundations of the main methods of Machine Learning. Do no expect code but pseudo code. 

http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511973000

Duda & Hart "Pattern Classification" is a pretty good, clear and complete introduction to ML.

http://www.amazon.ca/Pattern-Classification-Richard-O-Duda/dp/0471056693

Introduction to Machine Learning, second edition

By Ethem Alpaydin

ISBN: 9780262012430

Introduction to Machine Learning, second edition

By Ethem Alpaydin

ISBN: 9780262012430

Introduction to Machine Learning, second edition

By Ethem Alpaydin

ISBN: 9780262012430

I would add to the above 

An Introduction to Statistical Learning with Applications in R

Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

http://www-bcf.usc.edu/~gareth/ISL/

This is not a book, but a description of a robot brain, based on learning. It has many ideas on a biologocally inspired computer program that is a brain.

http://www.intelligent-systems.com.ar/intsyst/robotBrain.htm

Apart from the answer provided by Dr. Kostas, a very good introductory book on machine learning would be

Machine Learning, by Tom M. Mitchell.

ISBN: 0070428077

Hi David,

the one from Pr Hastie and Pr Tidhshirani and guess they are free in electronic format, thank to both Professor, you can have their last one as well  not one introduction but as the others great :)

Read well 

Alain

http://statweb.stanford.edu/~tibs/ElemStatLearn/

http://www-bcf.usc.edu/~gareth/ISL/

"Introduction to Statistical Machine Learning" By Masashi Sugiyama

https://www.elsevier.com/books/introduction-to-statistical-machine-learning/sugiyama/978-0-12-802121-7