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Data Science  with Python

You're reading from   Data Science with Python Combine Python with machine learning principles to discover hidden patterns in raw data

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Product type Paperback
Published in Jul 2019
Publisher Packt
ISBN-13 9781838552862
Length 426 pages
Edition 1st Edition
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Authors (3):
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Rohan Chopra Rohan Chopra
Author Profile Icon Rohan Chopra
Rohan Chopra
Mohamed Noordeen Alaudeen Mohamed Noordeen Alaudeen
Author Profile Icon Mohamed Noordeen Alaudeen
Mohamed Noordeen Alaudeen
Aaron England Aaron England
Author Profile Icon Aaron England
Aaron England
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Toc

Table of Contents (10) Chapters Close

About the Book 1. Introduction to Data Science and Data Pre-Processing FREE CHAPTER 2. Data Visualization 3. Introduction to Machine Learning via Scikit-Learn 4. Dimensionality Reduction and Unsupervised Learning 5. Mastering Structured Data 6. Decoding Images 7. Processing Human Language 8. Tips and Tricks of the Trade 1. Appendix

Dimensionality Reduction and Unsupervised Learning

Learning Objectives

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

  • Compare hierarchical cluster analysis (HCA) and k-means clustering
  • Conduct an HCA and interpret the output
  • Tune a number of clusters for k-means clustering
  • Select an optimal number of principal components for dimension reduction
  • Perform supervised dimension compression using linear discriminant function analysis (LDA)

This chapter will cover various concepts that fall under dimensionality reduction and unsupervised learning.

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