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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Length 642 pages
Edition 2nd Edition
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Authors (2):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (18) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 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

Deploying machine learning models

Bringing into production a project based on machine learning isn't easy. In fact, there are only a few companies that have managed to do it, at least for large projects. The difficulties lie in the fact that artificial intelligence is not something that is produced with finished software. A starting platform is needed to implement its own software model encountering problems that are not analogous to those that the developers usually encounter. The classic approach of software engineering leads to abstraction so that you arrive at simple code that can be modified and improved. Unfortunately, it is difficult to pursue abstraction in machine learning applications, just as it is difficult to control the complexity of machine learning. The best thing to do is focus on a platform that has the functions you need and, at the same time, allows you...

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