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Python Data Mining Quick Start Guide

You're reading from   Python Data Mining Quick Start Guide A beginner's guide to extracting valuable insights from your data

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789800265
Length 188 pages
Edition 1st Edition
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Author (1):
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Nathan Greeneltch Nathan Greeneltch
Author Profile Icon Nathan Greeneltch
Nathan Greeneltch
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Table of Contents (9) Chapters Close

Preface 1. Data Mining and Getting Started with Python Tools 2. Basic Terminology and Our End-to-End Example FREE CHAPTER 3. Collecting, Exploring, and Visualizing Data 4. Cleaning and Readying Data for Analysis 5. Grouping and Clustering Data 6. Prediction with Regression and Classification 7. Advanced Topics - Building a Data Processing Pipeline and Deploying It 8. Other Books You May Enjoy

Basic Terminology and Our End-to-End Example

The philosophy behind a quick-start guide is that the topic at hand is best learned by doing. In this chapter, I will present a quick overview of important vocabulary, concepts, and terminology that you need to get started, and then jump directly into a full end-to-end working example of data mining in Python. Later chapters will flesh out the steps in the working example in more detail.

The following topics will be covered in this chapter:

  • Basic data terminology
  • Basic statistics
  • An end-to-end example of data mining in Python
You have been reading a chapter from
Python Data Mining Quick Start Guide
Published in: Apr 2019
Publisher: Packt
ISBN-13: 9781789800265
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