May 2019
Beginner to intermediate
266 pages
5h 57m
English
Content preview from Hands-On Exploratory Data Analysis with R
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Summary
In this chapter, we have focused on the implementation of all libraries for handling optimization as well as regression data problems from the data frame indicated. The best illustration that is considered is to check the various parameters of the Glass Identification dataset where it includes various parameters of minerals for assessment, such as Na, Mg, and many more. We have listed some of the various packages that are available for reading in various kinds of attributes within the dataset mentioned in R. In the later sections, we covered the various correlation aspects that help to maintain linear regression analysis for the data frame indicated.
In the next chapter, we will cover how to build a roadmap for you to build on the ...
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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.