February 2019
Intermediate to advanced
386 pages
9h 54m
English
Content preview from Hands-On Unsupervised Learning with Python
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Clustering Fundamentals
In this chapter, we are going to introduce the fundamental concept of cluster analysis, focusing the attention on our main principles that are shared by many algorithms and the most important techniques that can be employed to evaluate the performance of a method.
In particular, we are going to discuss:
- An introduction to clustering and distance functions
- K-means and K-means++
- Evaluation metrics
- K-Nearest Neighbors (KNN)
- Vector Quantization (VQ)
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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.