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Learning Data Mining with Python

You're reading from   Learning Data Mining with Python Use Python to manipulate data and build predictive models

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787126787
Length 358 pages
Edition 2nd Edition
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Concepts
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Data Mining FREE CHAPTER 2. Classifying with scikit-learn Estimators 3. Predicting Sports Winners with Decision Trees 4. Recommending Movies Using Affinity Analysis 5. Features and scikit-learn Transformers 6. Social Media Insight using Naive Bayes 7. Follow Recommendations Using Graph Mining 8. Beating CAPTCHAs with Neural Networks 9. Authorship Attribution 10. Clustering News Articles 11. Object Detection in Images using Deep Neural Networks 12. Working with Big Data 13. Next Steps...

Getting Started with Data Mining

We are collecting information about our world on a scale that has never been seen before in the history of humanity. Along with this trend, we are now placing more day-to-day importance on the use of this information in everyday life. We now expect our computers to translate web pages into other languages, predict the weather with high accuracy, suggest books we would like, and to diagnose our health issues. These expectations will grow into the future, both in application breadth and efficacy. Data Mining is a methodology that we can employ to train computers to make decisions with data and forms the backbone of many high-tech systems of today.

The Python programming language is fast growing in popularity, for a good reason. It gives the programmer flexibility, it has many modules to perform different tasks, and Python code is usually more readable and concise than in any other languages. There is a large and an active community of researchers, practitioners, and beginners using Python for data mining.

In this chapter, we will introduce data mining with Python. We will cover the following topics

  • What is data mining and where can we use it?
  • Setting up a Python-based environment to perform data mining
  • An example of affinity analysis, recommending products based on purchasing habits
  • An example of (a classic) classification problem, predicting the plant species based on its measurement
You have been reading a chapter from
Learning Data Mining with Python - Second Edition
Published in: Apr 2017
Publisher: Packt
ISBN-13: 9781787126787
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