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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

3. Preparing Data for Predictive Modeling

Overview

In this chapter, you will learn to plan a machine learning strategy and assess whether or not data is suitable for modeling. You will also perform operations on data in to prepare it so that it can be used to train models. This will include filling missing records, converting from categorical to numeric features, and splitting datasets into training and testing groups. By the end of this chapter, you will be able to process datasets and make them ready for predictive analysis.

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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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