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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

Bivariate EDA

Now that we understand our features individually, it is time to start exploring whether there are any relationships between them. Bivariate EDA techniques are used to explore pairs of variables, and start understanding how they relate to each other.

How many pair relationships will we have? For a dataset of k features, we will have distinct pairs. In our original dataset we have 10 features, so we will have pairs of variables to analyze. This is a very small dataset, (in terms of the number of features)—but as you can see, the formula is basically a quadratic term, so for a large dataset, the number of pairs goes up quickly.

Of course, you don't actually have to analyze every possible pair; only choose those that are interesting or which will answer a particular question you may have about the dataset. In addition, pandas and Seaborn will make our task...

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