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Hands-On Predictive Analytics with Python

You're reading from   Hands-On Predictive Analytics with Python Master the complete predictive analytics process, from problem definition to model deployment

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789138719
Length 330 pages
Edition 1st Edition
Languages
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Author (1):
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Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
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Table of Contents (11) Chapters Close

Preface 1. The Predictive Analytics Process FREE CHAPTER 2. Problem Understanding and Data Preparation 3. Dataset Understanding – Exploratory Data Analysis 4. Predicting Numerical Values with Machine Learning 5. Predicting Categories with Machine Learning 6. Introducing Neural Nets for Predictive Analytics 7. Model Evaluation 8. Model Tuning and Improving Performance 9. Implementing a Model with Dash 10. Other Books You May Enjoy

Summary

In this chapter, we learned some of the most basic and useful techniques for performing EDA. We provided many examples of how to produce visualizations and numerical calculations, and how to interpret them.

We learned about the main techniques for univariate and bivariate analysis, including histograms, bar plots, scatter plots, and boxplots. We also provided some examples of complex multivariate visualizations with Seaborn.

Please bear in mind that the reason for applying all these techniques is to understand the dataset, which will give us a better picture of the relationship between the business problem and the data. It also provides us with valuable information for the next stage of the process: predictive modeling, that will be the subject of our next chapter

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