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Building Machine Learning Systems with Python

You're reading from   Building Machine Learning Systems with Python Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need.

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Product type Paperback
Published in Jul 2013
Publisher Packt
ISBN-13 9781782161400
Length 290 pages
Edition 1st Edition
Languages
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Table of Contents (20) Chapters Close

Building Machine Learning Systems with Python
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with Python Machine Learning FREE CHAPTER 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

Summary


We learned that sometimes we can get rid of all the features using feature selection methods. We also saw that in some cases this is not enough, and we have to employ feature extraction methods that reveal the real and the lower-dimensional structure in our data, hoping that the model has an easier game with it.

We have only scratched the surface of the huge body of available dimensionality reduction methods. Still, we hope that we have got you interested in this whole field, as there are lots of other methods waiting for you to pick up. At the end, feature selection and extraction is an art, just like choosing the right learning method or training model.

The next chapter covers the use of Jug, a little Python framework to manage computations in a way that takes advantage of multiple cores or multiple machines. We will also learn about AWS – the Amazon cloud.

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