July 2019
Beginner to intermediate
298 pages
7h 20m
English
Content preview from Hands-On Ensemble Learning with Python
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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.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.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.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.
Demystifying recommendation systems
Although the inner workings of recommendation systems may seem intimidating at first, they are actually quite intuitive. Let's take an example of various movies and users. Each user has the option to rate a movie on a scale of 1 to 5. The recommendation system will try to find users with similar preferences to a new user, and will then recommend movies that the new user will probably like, as similar users also like them. Let's take the following simple example, consisting of four users and six movies:
|
User |
Interstellar |
2001: A Space Odyssey |
The Matrix |
Full Metal Jacket |
Jarhead |
Top Gun |
|
U0 |
5 |
4 |
2 |
1 |
||
|
U1 |
1 |
4 |
4 |
3 |
||
|
U2 |
4 |
4 |
1 |
|||
|
U3 |
4 |
5 |
5 |
4 |
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