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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

Summary

This chapter covered the basic statistics and data terminology that are required for working in data mining. The final portion of the chapter was dedicated to a full working example, which combined the types of techniques that will be introduced later on in this book. After reading this chapter, you should have a better understanding of the thought processes behind analysis and the common steps taken to address a problem statement that you may encounter in the field. The subsequent chapters will explore each aspect of the example in more depth, with the next chapter focusing on collecting data, loading it into memory, and exploring it with ease.

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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