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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

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800200708
Length 550 pages
Edition 1st Edition
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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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Toc

Table of Contents (11) Chapters Close

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

5. Autoencoders

Overview

In this chapter, we will look at autoencoders and their applications. We will see how autoencoders are used in dimensionality reduction and denoising. We will implement an artificial neural network and an autoencoder using the Keras framework. By the end of this chapter, you will be able to implement an autoencoder model using convolutional neural networks.

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