As a software engineer, I'm interested in topics such as statistical algorithms, data mining, machine learning, Bayesian networks, classification algorithms, neural networks, Markov chains, Monte Carlo methods, and random number generation.

I personally haven't had the pleasure of working hands-on with any of these techniques, but I have had to work with software that, under the hood, employed them and would like to know more about them, at a high level. I'm looking for books that cover a great breadth - great depth is not necessary at this point. I think that I can learn a lot about software development if I can understand the mathematical foundations behind the algorithms and techniques that are employed.

Can the Statistical Analysis community recommend books that I can use to learn more about implementing various statistical elements in software?

(Also, could someone add the tags computational-statistics and computing to this question? Thanks.)

As a software engineer, I'm interested in topics such as statistical algorithms, data mining, machine learning, Bayesian networks, classification algorithms, neural networks, Markov chains, Monte Carlo methods, and random number generation.

I personally haven't had the pleasure of working hands-on with any of these techniques, but I have had to work with software that, under the hood, employed them and would like to know more about them, at a high level. I'm looking for books that cover a great breadth - great depth is not necessary at this point. I think that I can learn a lot about software development if I can understand the mathematical foundations behind the algorithms and techniques that are employed.

Can the Statistical Analysis community recommend books that I can use to learn more about implementing various statistical elements in software?