October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Clustering
Congratulations! You have finished this book's introductory section, in which you have explored a great number of topics, and if you were able to follow it, you are prepared to start the journey of understanding the inner workings of many machine learning models.
In this chapter, we will explore some effective and simple approaches for automatically finding interesting data conglomerates, and so begin to research the reasons for natural groupings in data.
This chapter will covers the following topics:
- A line-by-line implementation of an example of the K-means algorithm, with explanations of the data structures and routines
- A thorough explanation of the k-nearest neighbors (K-NN) algorithm, using a code example to explain the whole ...
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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.