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Applied Data Science with Python and Jupyter

You're reading from Applied Data Science with Python and Jupyter Use powerful industry-standard tools to unlock new, actionable insights from your data

Product type Paperback

Published in Oct 2018

Publisher

ISBN-13 9781789958171

Length 192 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Author (1):

Alex Galea

View More author details

Table of Contents (5) Chapters

Preface

About the Book

1. Jupyter Fundamentals

2. Data Cleaning and Advanced Machine Learning FREE CHAPTER

3. Web Scraping and Interactive Visualizations

Appendix A

Jupyter Fundamentals

Learning Objectives

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

Describe Jupyter Notebooks and how they are used for data analysis
Describe the features of Jupyter Notebooks
Use Python data science libraries
Perform simple exploratory data analysis

In this chapter, you will learn and implement the fundamental features of the Jupyter notebook by completing several hands-on erxercises.

The rest of the chapter is locked

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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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