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Learning Data Mining with Python

You're reading from   Learning Data Mining with Python Harness the power of Python to analyze data and create insightful predictive models

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Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781784396053
Length 344 pages
Edition 1st Edition
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Author (1):
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Robert Layton Robert Layton
Author Profile Icon Robert Layton
Robert Layton
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Table of Contents (15) 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. Extracting Features with Transformers 6. Social Media Insight Using Naive Bayes 7. Discovering Accounts to Follow Using Graph Mining 8. Beating CAPTCHAs with Neural Networks 9. Authorship Attribution 10. Clustering News Articles 11. Classifying Objects in Images Using Deep Learning 12. Working with Big Data A. Next Steps… Index

What you need for this book

It should come as no surprise that you'll need a computer, or access to one, to complete this book. The computer should be reasonably modern, but it doesn't need to be overpowered. Any modern processor (from about 2010 onwards) and 4 GB of RAM will suffice, and you can probably run almost all of the code on a slower system too.

The exception here is with the final two chapters. In these chapters, I step through using Amazon Web Services (AWS) to run the code. This will probably cost you some money, but the advantage is less system setup than running the code locally. If you don't want to pay for those services, the tools used can all be set up on a local computer, but you will definitely need a modern system to run it. A processor built in at least 2012 and with more than 4 GB of RAM is necessary.

I recommend the Ubuntu operating system, but the code should work well on Windows, Macs, or any other Linux variant. You may need to consult the documentation for your system to get some things installed, though.

In this book, I use pip to install code, which is a command-line tool for installing Python libraries. Another option is to use Anaconda, which can be found online here: http://continuum.io/downloads.

I have also tested all code using Python 3. Most of the code examples work on Python 2, with no changes. If you run into any problems and can't get around them, send an email and we can offer a solution.

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