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Building Machine Learning Systems with Python

You're reading from  Building Machine Learning Systems with Python

Product type Book
Published in Jul 2013
Publisher Packt
ISBN-13 9781782161400
Pages 290 pages
Edition 1st Edition
Languages

Table of Contents (20) Chapters

Building Machine Learning Systems with Python
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with Python Machine Learning 2. Learning How to Classify with Real-world Examples 3. Clustering – Finding Related Posts 4. Topic Modeling 5. Classification – Detecting Poor Answers 6. Classification II – Sentiment Analysis 7. Regression – Recommendations 8. Regression – Recommendations Improved 9. Classification III – Music Genre Classification 10. Computer Vision – Pattern Recognition 11. Dimensionality Reduction 12. Big(ger) Data Where to Learn More about Machine Learning Index

Learning about big data


The expression "big data" does not mean a specific amount of data, neither in the number of examples nor in the number of gigabytes, terabytes, or petabytes taken up by the data. It means the following:

  • We have had data growing faster than the processing power

  • Some of the methods and techniques that worked well in the past now need to be redone, as they do not scale well

  • Your algorithms cannot assume that the entire data is in RAM

  • Managing data becomes a major task in itself

  • Using computer clusters or multicore machines becomes a necessity and not a luxury

This chapter will focus on this last piece of the puzzle: how to use multiple cores (either on the same machine or on separate machines) to speed up and organize your computations. This will also be useful in other medium-sized data tasks.

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