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Machine Learning for Developers

You're reading from   Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786469878
Length 270 pages
Edition 1st Edition
Languages
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Authors (2):
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Md Mahmudul Hasan Md Mahmudul Hasan
Author Profile Icon Md Mahmudul Hasan
Md Mahmudul Hasan
Rodolfo Bonnin Rodolfo Bonnin
Author Profile Icon Rodolfo Bonnin
Rodolfo Bonnin
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction - Machine Learning and Statistical Science 2. The Learning Process FREE CHAPTER 3. Clustering 4. Linear and Logistic Regression 5. Neural Networks 6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Recent Models and Developments 9. Software Installation and Configuration

Automating the clustering process

The grouping of information for clustering follows a common pattern for all techniques. Basically, we have an initialization stage, followed by the iterative insertion of new elements, after which the new group relationships are updated. This process continues until the stop criteria is met, where the group characterization is finished. The following flow diagram illustrates this process:

General scheme for a clustering algorithm

After we get a clear sense of the overall process, let's start working with several cases where this scheme is applied, starting with K-means.

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