November 2017
Beginner to intermediate
366 pages
7h 59m
English
Content preview from R Data Analysis Projects
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Summary
We started the chapter with an overview of recommender systems. We introduced our retail case and the association rule mining algorithm. Then we applied association rule mining to design a cross-selling campaign. We went on to understand weighted association rule mining and its applications. Following that, we introduced the HITS algorithm and its use in transaction data. Next, we studied the negative association rules discovery process and its use. We showed you different ways to visualize association rules. Finally, we created a small web application using R Shiny to demonstrate some of the concepts we learned.
In the next chapter, we will look at another recommendation system algorithm called content based filtering. We will see ...
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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.