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The Unsupervised Learning Workshop

You're reading from The Unsupervised Learning Workshop Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800200708

Length 550 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Machine Learning

Authors (3):

Benjamin Johnston

Christopher Kruger

Aaron Jones

View More author details

Table of Contents (11) Chapters

Preface

1. Introduction to Clustering

2. Hierarchical Clustering FREE CHAPTER

3. Neighborhood Approaches and DBSCAN

4. Dimensionality Reduction Techniques and PCA

5. Autoencoders

6. t-Distributed Stochastic Neighbor Embedding

7. Topic Modeling

8. Market Basket Analysis

9. Hotspot Analysis

Appendix

9. Hotspot Analysis

Overview

In this chapter, we will perform hotspot analysis. We will also visualize the results of hotspot analysis. We will use kernel density estimation, which is the most popular algorithm for building distributions using a collection of observations. We will build kernel density estimation models. We will describe the fundamentals behind probability density functions. By the end of the chapter, you should be able to leverage Python libraries to build multi-dimensional density estimation models and work with geo-spatial data.

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Authors (3)

Aaron Jones

Aaron Jones

Aaron Jones is a full-time senior data scientist and consultant. He has built models and data products while working in retail, media, and environmental science. Aaron is based in Seattle, Washington and has a particular interest in clustering algorithms, natural language processing, and Bayesian statistics.

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Christopher Kruger

Christopher Kruger

Christopher Kruger is a practicing data scientist and AI researcher. He has managed applied machine learning projects across multiple industries while mentoring junior team members on best practices. His primary focus is on pushing both business practicality as well as academic rigor in every project. Chris is currently developing research in the computer vision space.

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Benjamin Johnston

Benjamin Johnston

Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.

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