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Building Machine Learning Systems with Python

You're reading from   Building Machine Learning Systems with Python Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788623223
Length 406 pages
Edition 3rd Edition
Languages
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Authors (3):
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Luis Pedro Coelho Luis Pedro Coelho
Author Profile Icon Luis Pedro Coelho
Luis Pedro Coelho
Willi Richert Willi Richert
Author Profile Icon Willi Richert
Willi Richert
Matthieu Brucher Matthieu Brucher
Author Profile Icon Matthieu Brucher
Matthieu Brucher
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Machine Learning FREE CHAPTER 2. Classifying with Real-World Examples 3. Regression 4. Classification I – Detecting Poor Answers 5. Dimensionality Reduction 6. Clustering – Finding Related Posts 7. Recommendations 8. Artificial Neural Networks and Deep Learning 9. Classification II – Sentiment Analysis 10. Topic Modeling 11. Classification III – Music Genre Classification 12. Computer Vision 13. Reinforcement Learning 14. Bigger Data 15. Where to Learn More About Machine Learning 16. Other Books You May Enjoy

Clustering

Finally, we have our vectors, which we believe capture the posts to a sufficient degree. Not surprisingly, there are many ways to group them together. One way to classify clustering algorithms is to distinguish between flat and hierarchical clustering.

Flat clustering divides the posts into a set of clusters without relating the clusters to each other. The goal is simply to come up with a partition such that all posts in one cluster are most similar to each other while being dissimilar from the posts in all other clusters. Many flat clustering algorithms require the number of clusters to be specified up front.

In hierarchical clustering, the number of clusters does not have to be specified. Instead, hierarchical clustering creates a hierarchy of clusters. While similar posts are grouped into one cluster, similar clusters are again grouped into one uber-cluster. In the...

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