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Python Data Science Essentials

You're reading from   Python Data Science Essentials A practitioner's guide covering essential data science principles, tools, and techniques

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789537864
Length 472 pages
Edition 3rd Edition
Languages
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
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Toc

Table of Contents (11) Chapters Close

Preface 1. First Steps FREE CHAPTER 2. Data Munging 3. The Data Pipeline 4. Machine Learning 5. Visualization, Insights, and Results 6. Social Network Analysis 7. Deep Learning Beyond the Basics 8. Spark for Big Data 9. Strengthen Your Python Foundations 10. Other Books You May Enjoy

Summary

This chapter provided an overview of essential data science by providing examples of both basic and advanced graphical representations of data, machine learning processes, and results. We explored the pylab module from matplotlib, which gives the easiest and fastest access to the graphical capabilities of the package. We used pandas for EDA, and tested the graphical utilities provided by scikit-learn. All examples were like building blocks, and they are all easily customizable in order to provide you with a fast template for visualization.

In the next chapter, you'll be introduced to graphs, which are an interesting deviation from the predictors/target flat matrices. They are quite a hot topic in data science now. Expect to delve into very complex and intricate networks.

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