Following on from my recent post stats for hackers introducing statistics and non-deterministic programming concepts, if you feel you want to take the next step, Mike de Waard has provided a very accessible guide to some of the high level topics of Machine Learning. In his own words;

Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learning and terms as regression, unsupervised learning, Probability Density Function and many other definitions. If one switches to books there are books such as An Introduction to Statistical Learning with Applications in R and Machine Learning for Hackers who use programming language R for their examples.

That said, I am not convinced about using Java as the Lingua Franca for the topic. Java is not exactly known for its succinct, concise representations of concepts (just my personal thoughts).

Check out the full article here

If you really want to push the boat out and gain a deeper understanding of the subject then I can recommend highly enough, Andrew Ng's Stanford/Coursera Machine Learning course. Andrew is one of the pioneers of the field and understands it at even the deepest levels however still manages to make the subject accessible.