Learning About Machine Learning 2nd Ed. (opens in new tab)

IMO, AI is logically quite different from Machine Learning / Statistical Learning.

The stuff mentioned on this page is largely about methods to learn from structured or unstructured data, and this is a field that has become highly relevant of late due to the data deluge. Research in these areas has progressed immensely as well, and we now have methods to mine many different types and volumes of data. If you have a good grip of statistical techniques and some basic ML ideas, you will be able to single out and pick the right technique that fits your problem, given your data type, SNR ratio, structured-ness, volume, your resource constraints, etc. Knowing a little more about ML will also allow you to change/invent new methods to suit your own problems better (e.g., a new way to compress your feature space).

"for folks who just want to their feet wet, oreilly's programming collective intelligence is a good start."

No, it is not a good start.

I own them all, and I am perpetually at different stages of working through each of them. :-) I work in the way I explained in the intro - when I don't know something, I step back and go learn the background I need to move forward.

Nice catch.