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Building Machine Learning Systems with Python

You're reading from   Building Machine Learning Systems with Python Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788623223
Length 406 pages
Edition 3rd Edition
Languages
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Authors (3):
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Luis Pedro Coelho Luis Pedro Coelho
Author Profile Icon Luis Pedro Coelho
Luis Pedro Coelho
Willi Richert Willi Richert
Author Profile Icon Willi Richert
Willi Richert
Matthieu Brucher Matthieu Brucher
Author Profile Icon Matthieu Brucher
Matthieu Brucher
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Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Machine Learning FREE CHAPTER 2. Classifying with Real-World Examples 3. Regression 4. Classification I – Detecting Poor Answers 5. Dimensionality Reduction 6. Clustering – Finding Related Posts 7. Recommendations 8. Artificial Neural Networks and Deep Learning 9. Classification II – Sentiment Analysis 10. Topic Modeling 11. Classification III – Music Genre Classification 12. Computer Vision 13. Reinforcement Learning 14. Bigger Data 15. Where to Learn More About Machine Learning 16. Other Books You May Enjoy

Bigger Data

It's not easy to say what big data is. We will adopt an operational definition: when data is so large that it becomes cumbersome to work with, we refer to it as big data. In some cases, this might mean petabytes of data or trillions of transactions: data that will not fit into a single hard drive. In other cases, it may be one hundred times smaller, but still difficult to work with.

Why has data itself become an issue? While computers keep getting faster and gaining more memory, the size of the data has grown as well. In fact, data has grown faster than computational speed and few algorithms scale linearly with the size of the input data taken together; this means that data has grown faster than our ability to process it.

We will first build on some of the experience of the previous chapters and work with what we can call medium data setting (not quite big data...

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