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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

Product type Paperback

Published in Apr 2017

Publisher Packt

ISBN-13 9781787126787

Length 358 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Mining

Table of Contents (14) Chapters

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...

Working with Big Data

The following resources on Big Data would be helpful

Courses on Hadoop

Both Yahoo and Google have great tutorials on Hadoop, which go from beginner to quite advanced levels. They don't specifically address using Python, but learning the Hadoop concepts and then applying them in Pydoop or a similar library can yield great results.

Yahoo's tutorial: https://developer.yahoo.com/hadoop/tutorial/

Google's tutorial: https://cloud.google.com/hadoop/what-is-hadoop

Pydoop

URL: http://crs4.github.io/pydoop/tutorial/index.html

Pydoop is a python library to run Hadoop jobs. Pydoop also works with HDFS, the Hadoop File System, although you can get that functionality in mrjob as well. Pydoop will give you a bit more control over running some jobs.

Recommendation engine

Building a large recommendation engine is a good test of your Big data skills. A great blog post by Mark Litwintschik covers an engine using Apache Spark, a big data technology: http://tech.marksblogg.com/recommendation-engine...

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