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Python Machine Learning Cookbook, - Second Edition

You're reading from  Python Machine Learning Cookbook, - Second Edition

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Pages 642 pages
Edition 2nd Edition
Languages
Authors (2):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (18) Chapters close

Preface 1. The Realm of Supervised Learning 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Working with auto-sklearn

Auto-sklearn works on the scikit-learn machine learning library. It represents a platform based on supervised machine learning that's ready for use. It automatically searches for the correct machine learning algorithm for a new dataset and optimizes its hyperparameters.

Getting ready

In this recipe, you will learn how to use auto-sklearn to build a classifier. To import the data, the sklearn.datasets.load_digits function will be used. This function loads and returns the digits dataset for classification problems. Each datapoint is an 8x8 image of a digit.

How to do it...

...
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