I've gone through this book. I found it useful for theory, but not useful for gaining an appreciation of how the models work in practice. Most practitioners will appreciate a more applied book than this one.
http://shop.oreilly.com/product/0636920018483.do http://www.amazon.com/Machine-Learning-for-Hackers-ebook/dp/...
It's definitely a practical approach. There's a lot of explanation but, despite coming from two PhD candidates, it certainly did not read like an academic paper.
It's also case study based, not necessarily algorithm based.
As a bonus, I used that book to teach myself R. I don't think it's meant to be an intro to R tutorial, but it worked for me.
All three are positives in my book.
http://www.amazon.com/Pattern-Classification-2nd-Richard-Dud...
It is very pragmatic, including algorithms for many machine learning and artificial intelligence topics (from fitting functions for classification or regression purposes to search processes). The authors have a strong industrial background (in addition to the academic).