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Applied Unsupervised Learning with Python

You're reading from   Applied Unsupervised Learning with Python Discover hidden patterns and relationships in unstructured data with Python

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Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781789952292
Length 482 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Christopher Kruger Christopher Kruger
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Christopher Kruger
Aaron Jones Aaron Jones
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Aaron Jones
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Table of Contents (12) Chapters Close

Applied Unsupervised Learning with Python
Preface
1. Introduction to Clustering FREE CHAPTER 2. Hierarchical Clustering 3. Neighborhood Approaches and DBSCAN 4. Dimension Reduction and PCA 5. Autoencoders 6. t-Distributed Stochastic Neighbor Embedding (t-SNE) 7. Topic Modeling 8. Market Basket Analysis 9. Hotspot Analysis Appendix

Chapter 9. Hotspot Analysis

Note

Learning Objectives

By the end of this chapter, you will be able to:

  • Understand some of the applications of spatial modeling

  • Deploy hotspot models in the appropriate context

  • Build kernel density estimation models

  • Perform hotspot analysis and visualize the results

Note

In this chapter, we will learn about kernel density estimation and learn how to perform hotspot analysis.

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