If your math background is weak enough that you don't feel totally at home using calculus and linear algebra, I'd recommend "Principles of Data Mining", which they use for the intro to ML class at Princeton. The ratio of English to equations is pretty high, which might help you to get into the swing of things.

If you think that you can learn enough math to follow the material, you should watch the Stanford lectures given by Andrew Ng. They're available freely online through iTunes U. Andrew is also one of the most respected experts in the field. As he points out, you will eventually need to understand the math behind the methods. Otherwise, a day will come when you start wasting time coding algorithms that plainly don't apply to the problem at hand.