September 2015
Beginner to intermediate
608 pages
13h 43m
English
Content preview from Clojure for Data Science
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Chapter 4. Classification
"It is a truth universally acknowledged, that a single man in possession of a good fortune, must be in want of a wife." | ||
| --Jane Austen, Pride and Prejudice | ||
In the previous chapter, we learned how to make numeric predictions using linear regression. The model we built was able to learn how the features of Olympic swimmers related to their weight and we were able to use the model to make a weight prediction for a new swimmer. As with all regression techniques, our output was a number.
Not all predictions demand a numeric solution, though—sometimes we want our predictions to be items. For example, we may want to predict which candidate a voter will back in an election. Or we may want to know which of several products a customer ...
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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.