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Hands-On Exploratory Data Analysis with Python

You're reading from   Hands-On Exploratory Data Analysis with Python Perform EDA techniques to understand, summarize, and investigate your data

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789537253
Length 352 pages
Edition 1st Edition
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Authors (2):
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Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
Usman Ahmed Usman Ahmed
Author Profile Icon Usman Ahmed
Usman Ahmed
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Table of Contents (17) Chapters Close

Preface 1. Section 1: The Fundamentals of EDA
2. Exploratory Data Analysis Fundamentals FREE CHAPTER 3. Visual Aids for EDA 4. EDA with Personal Email 5. Data Transformation 6. Section 2: Descriptive Statistics
7. Descriptive Statistics 8. Grouping Datasets 9. Correlation 10. Time Series Analysis 11. Section 3: Model Development and Evaluation
12. Hypothesis Testing and Regression 13. Model Development and Evaluation 14. EDA on Wine Quality Data Analysis 15. Other Books You May Enjoy Appendix

Unified machine learning workflow

The choice of what machine learning algorithm to use always depends on the type of data you have. If you have a labeled dataset, then your obvious choice will be to select one of the supervised machine learning techniques. Moreover, if your labeled dataset contains real values in the target variable, then you will opt for regression algorithms. Finally, if your labeled dataset contains a categorical variable in the target variable, then you will opt for the classification algorithm. In any case, the algorithm you choose always depends on the type of dataset you have.

In a similar fashion, if your dataset does not contain any target variables, then the obvious choice is unsupervised algorithms. In this section, we are going to look at the unified approach to machine learning.

The machine learning workflow can be divided into several stages:

    ...
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