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The Data Science Workshop

You're reading from   The Data Science Workshop A New, Interactive Approach to Learning Data Science

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Product type Paperback
Published in Jan 2020
Publisher
ISBN-13 9781838981266
Length 818 pages
Edition 1st Edition
Languages
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Authors (5):
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Thomas Joseph Thomas Joseph
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Thomas Joseph
Andrew Worsley Andrew Worsley
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Andrew Worsley
Robert Thas John Robert Thas John
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Robert Thas John
Anthony So Anthony So
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Anthony So
Dr. Samuel Asare Dr. Samuel Asare
Author Profile Icon Dr. Samuel Asare
Dr. Samuel Asare
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introduction to Data Science in Python 2. Regression FREE CHAPTER 3. Binary Classification 4. Multiclass Classification with RandomForest 5. Performing Your First Cluster Analysis 6. How to Assess Performance 7. The Generalization of Machine Learning Models 8. Hyperparameter Tuning 9. Interpreting a Machine Learning Model 10. Analyzing a Dataset 11. Data Preparation 12. Feature Engineering 13. Imbalanced Datasets 14. Dimensionality Reduction 15. Ensemble Learning 16. Machine Learning Pipelines 17. Automated Feature Engineering

14. Dimensionality Reduction

Overview

This chapter introduces dimensionality reduction in data science. You will be using the Internet Advertisements dataset to analyze and evaluate different techniques in dimensionality reduction. By the end of this chapter, you will be able to analyze datasets with high dimensions and deal with the challenges posed by these datasets. As well as applying different dimensionality reduction techniques to large datasets, you will fit models based on those datasets and analyze their results. By the end of this chapter, you will be able to deal with huge datasets in the real world.

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