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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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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...

The Enron dataset


Enron was one of the largest energy companies in the world in the late 1990s, reporting revenue over $100 billion. It had over 20,000 staff and—as of the year 2000—there seemed to be no indications that something was very wrong.

In 2001, the Enron Scandal occurred, where it was discovered that Enron was undertaking systematic, fraudulent accounting practices. This fraud was deliberate, wide-ranging across the company, and for significant amounts of money. After this was publicly discovered, its share price dropped from more than $90 in 2000 to less than $1 in 2001. Enron shortly filed for bankruptcy in a mess that would take more than 5 years to finally be resolved.

As part of the investigation into Enron, the Federal Energy Regulatory Commission in the United States made more than 600,000 e-mails publicly available. Since then, this dataset has been used for research into everything from social network analysis to fraud analysis. It is also a great dataset for authorship...

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