May 2019
Intermediate to advanced
162 pages
4h 24m
English
Content preview from Supervised Machine Learning with Python
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Recommended systems and an introduction to collaborative filtering
In this section, we'll cover collaborative filtering and recommender systems. We'll start out by explaining what may constitute a recommender system, how users willingly share loads of data about themselves, without knowing it, and then we'll cover collaborative filtering.
Whether you realize it or not, you interact with numerous recommender systems on a daily basis. If you've ever purchased from Amazon, or browsed on Facebook, or watched a show on Netflix, you've been served some form of personalized content. This is how e-commerce platforms maximize conversion rates and keep you coming back for more.
One of the marks of a really good recommender system is that it knows what ...
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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.