Unsupervised Learning with Python
Vaibhav Verdhan
  • MEAP began November 2020
  • Publication in Summer 2021 (estimated)
  • ISBN 9781617298721
  • 250 pages (estimated)
  • printed in black & white
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A practical guide to solving tricky business problems using Python-based unsupervised learning techniques.

Unsupervised Learning with Python contains comprehensive coverage of the mathematical foundations, algorithms, and practical implementations of unsupervised learning. In this focused guide, you’ll learn to use this hands-off machine learning approach to uncover patterns and trends in your data, and support sound strategic decisions for your business.

In Unsupervised Learning with Python, you’ll learn:

  • Fundamental building blocks and concepts of unsupervised learning
  • How to interpret the results of unsupervised learning
  • Deploying unsupervised learning to production
  • Best practices for debugging and improving your models
  • Data cleaning for structured and unstructured data
  • Choosing the right algorithm for your problem
  • Business use cases for unsupervised learning

About the Technology

Unsupervised learning algorithms draw inferences from unannotated data sets. The self-organizing approach to machine learning is great for spotting patterns a human might miss.

About the book

Unsupervised Learning with Python teaches you to apply the full spectrum of unsupervised learning algorithms. Each new algorithm is introduced with a case study for retail, aviation, banking, and more—and you’ll develop a Python solution to fix each of these real-world problems.

The book bridges the gap between complex math and practical Python implementations, covering end-to-end model development all the way through to production deployment. You’ll learn the business use case for different unsupervised learning models, and master best practices for structured, text, and image data. At the end of each chapter, you’ll find quizzes, practice datasets, and links to research papers to help you lock in what you’ve learned and expand your knowledge.

About the reader

For Python programmers. No machine learning experience required.

About the author

Vaibhav Verdhan is a seasoned data science professional with rich experience across geographies and domains. He has led multiple engagements in machine learning and artificial intelligence. A leading industry expert, Vaibhav is a regular speaker at conferences and meet-ups and mentors students and professionals. Currently he resides in Ireland where he works as a principal data scientist.

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