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Python Data Science Essentials. - Third Edition

You're reading from Python Data Science Essentials. - Third Edition

Product type Book

Published in Sep 2018

Publisher Packt

ISBN-13 9781789537864

Pages 472 pages

Edition 3rd Edition

Languages

Concepts

Author (1):

Alberto Boschetti

Table of Contents (11) Chapters

Preface

1. First Steps

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

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The Data Pipeline

Up until this point, we've explored how to load data into Python and process it to create a bidimensional NumPy array containing numerical values (your dataset). Now, we are ready to be immersed fully in data science, extract meaning from data, and develop potential data products. This chapter on data treatment and transformations and the next one on machine learning are the most challenging sections of this entire book.

In this chapter, you will learn how to do the following:

Briefly explore data and create new features
Reduce the dimensionality of data
Spot and treat outliers
Decide on the best score or loss metrics for your project
Apply scientific methodology and effectively test the performance of your machine learning hypothesis
Reduce the complexity of the data science problem by decreasing the number of features
Optimize your learning parameters...

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Authors (1)

Alberto Boschetti

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.

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