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

Product type Paperback

Published in May 2019

Publisher

ISBN-13 9781789952292

Length 482 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Authors (3):

Benjamin Johnston

Christopher Kruger

Aaron Jones

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Table of Contents (12) Chapters

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

Applied Unsupervised Learning with Python

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Authors: Benjamin Johnston, Aaron Jones, and Christopher Kruger

Technical Reviewer: Jay Kim

Managing Editor: Rutuja Yerunkar

Acquisitions Editor: Aditya Date

Production Editor: Nitesh Thakur

Editorial Board: David Barnes, Mayank Bhardwaj, Ewan Buckingham, Simon Cox, Mahesh Dhyani, Taabish Khan, Manasa Kumar, Alex Mazonowicz, Douglas Paterson, Dominic Pereira, Shiny Poojary, Erol Staveley, Ankita Thakur, Mohita Vyas, and Jonathan Wray

First Published: May 2019

Production Reference: 1240519

ISBN: 978-1-78995-229-2

Published by Packt Publishing Ltd.

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