April 2012
Intermediate to advanced
384 pages
11h 19m
English
Content preview from Machine Learning in Action
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Chapter 13. Using principal component analysis to simplify data
This chapter covers
- Dimensionality reduction techniques
- Principal component analysis
- Reducing the dimensionality of semiconductor data
Assume for a moment that you’re watching a sports match involving a ball on a flat monitor, not in person. The monitor probably contains a million pixels, and the ball is represented by, say, a thousand pixels. In most sports, we’re concerned with the position of the ball at a given time. For your brain to follow what’s going on, you need to follow the position of the ball on the playing field. You do this naturally, without even thinking about it. Behind the scene, you’re converting the million pixels on the monitor into ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.