May 2022
Beginner to intermediate
330 pages
7h 19m
English
Content preview from Building Data Science Solutions with Anaconda
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Chapter 8: Dealing with Common Data Problems
The ability to quickly assess the shortcomings of data and correct them can be the difference between being able to accomplish what you need to on time or falling behind. In this chapter, we're going to give you the tools to identify some of these problems, which you'll find are present in much of the data found in the industry.
We'll first look at when there can be too much data. This can be an issue where features can have an extremely high correlation with one another and in turn complicate a model. You'll see how to find this information and then remove the offending entries.
After that, we'll check into ways to get rid of blank, empty, or Not a Number (NaN) data that muddy the waters. This problem ...
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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.
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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.