Book: Machine Learning

Author: Tom M. Mitchell
Started: 25 Mar 2006
Finished: 18 Jun 2006
414p / 87d
5 p/d

This is a textbook I got for work to give me somewhat of a background in some of the technologies being used, and other related technologies that we might someday want to use. It is normally targeted at advanced undergrad CS majors or starting CS grad students. Now, I took a couple CS classes my freshman year of college, but really haven't done much else of the sort since then. So this was a mode of thinking I hadn't been much used to. And to be honest, even back then it was more about listening to and understanding a professor than trying to grok it by reading a book.

The first few chapters were pretty straightforward, but it did definitely get more challenging after that. And of course I wasn't doing it the full out way trying to actually do all the exercises and such at the end of every chapter. However I was, for the most part, doing careful reading. That is, if I read a paragraph or two and then realized I didn't fully understand what was being said, I'd go back and read it over and over again, thinking about it, until I thought I did understand. And sometimes that took a few passes. And even then, I think what I actually ABSORBED, in that I still remember after having finished the entire book, is just the general ideas for the most part, certainly not the details. If I was asked to actually do anything with any of the techniques described, I'd have to go back and read that chapter again with an even more fine tooth comb. And certainly, the further on you go in the book, the more true that is.

But it was still a good overview. Gives some good vocabulary I can use at work. And some background that helps me understand some of what the options and tradeoffs are. So it was good to have read it.

The next non-fiction will be a book for work as well. They are sneaking ahead in line of the personally chosen non-fiction. But for now, time for some light fiction...