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The Applied Data Science Workshop

You're reading from The Applied Data Science Workshop Get started with the applications of data science and techniques to explore and assess data effectively

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800202504

Length 352 pages

Edition 2nd Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Author (1):

Alex Galea

View More author details

Table of Contents (8) Chapters

Preface

Installing Libraries

1. Introduction to Jupyter Notebooks

2. Data Exploration with Jupyter FREE CHAPTER

3. Preparing Data for Predictive Modeling

4. Training Classification Models

5. Model Validation and Optimization

6. Web Scraping with Jupyter Notebooks

Appendix

5. Model Validation and Optimization

Overview

In this chapter, you will learn how to use k-fold cross validation to test model performance, as well as how to use validation curves to optimize model parameters. You will also learn how to implement dimensionality reduction techniques such as Principal Component Analysis (PCA). By the end of this chapter, you will have completed an end-to-end machine learning project and produced a final model that can be used to make business decisions.

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Authors (1)

Galea

Galea

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.

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