August 2015
Beginner to intermediate
294 pages
5h 20m
English
Content preview from Mastering Python for Data ScienceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
In this chapter, you learned the purpose of logistic regression. You learned how to build a logistic regression model using statsmodels and SciKit, and then how to evaluate the model and see whether it's a good model or not.
In the next chapter, you'll learn how to generate recommendations, such as the ones you see on http://www.amazon.com/, where you'll be recommended new items based on your purchase history. Similar items can also be shown to you based on the product that you are currently browsing.
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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.