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Hands-On Predictive Analytics with Python

You're reading from  Hands-On Predictive Analytics with Python

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781789138719
Pages 330 pages
Edition 1st Edition
Languages
Author (1):
Alvaro Fuentes Alvaro Fuentes
Profile icon Alvaro Fuentes

Table of Contents (11) Chapters

Preface 1. The Predictive Analytics Process 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

What is EDA?

As we stated in Chapter 1, The Predictive Analytics Process, EDA is a combination of numerical and visualization techniques that allow us to understand different characteristics of a dataset, its features, and the potential relationships between them.

Keep in mind the goal of this phase: to understand your dataset. The goal is not to produce summary statistics, pretty visualizations, or complex multivariate analysis. These are simple activities that accomplish the ultimate goal of data understanding.

Also, please don't confuse calculation with understanding. Anyone can calculate the standard deviation of a numerical feature; it can be done (for example) with the std() pandas Series method. Your job here is to use that number to understand your features and your dataset better.

Another example—after reading the definitions of symmetric and skewed distribution...

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