Olivier Langlois's blog

I like this book because it is a good compromise between lex & yacc man pages and the theory found in books such as the Dragon book. You will get valuable information about the how and why of the tools that will help you to produce a quality grammar without being overwhelmed by details.

This is the classical reference book for compiler design. This is not an easy text because of its heavy use of mathematical notation and the algorithms are presented only in pseudo code but you will not find a more complete collection of compiler related algorithms than in this book.

There is a new edition that I have not had the chance to review.

This is the book I used in my AI class. I have found it very well written and interesting to read and go through the very first neural networks models such as the Hebb net, the perceptron and the Adaline. Then the book continues by presenting simple neural network applications like pattern association.

I remember that our professor did ask the class to do one of the proposed projects in the pattern association chapter which consisted of implementing a small OCR with a neural network and this exercise did really help to better assimilate the principles. Finally, the following chapters present other types of neural networks such as those based on competition and the very important backpropagation neural network.

The only thing that you can complain about is its high price tag. For anyone interested in the AI field, it is recommended.