July 2017
Beginner to intermediate
420 pages
10h 56m
English
Content preview from Hands-On Data Science and Python Machine Learning
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Matplotlib and Advanced Probability Concepts
After going through some of the simpler concepts of statistics and probability in the previous chapter, we're now going to turn our attention to some more advanced topics that you'll need to be familiar with to get the most out of the remainder of this book. Don't worry, they're not too complicated. First of all, let's have some fun and look at some of the amazing graphing capabilities of the matplotlib library.
We'll be covering the following topics in this chapter:
- Using the matplotlib package to plot graphs
- Understanding covariance and correlation to determine the relationship between data
- Understanding conditional probability with examples
- Understanding Bayes' theorem and its importance
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.