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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
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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

Optimizing a financial portfolio using DP

The management of financial portfolios is an activity that aims to combine financial products in a manner that best represents the investor's needs. This requires an overall assessment of various characteristics, such as risk appetite, expected returns, and investor consumption, as well as an estimate of future returns and risk. Dynamic programming (DP) represents a set of algorithms that can be used to calculate an optimal policy given a perfect model of the environment in the form of an MDP. The fundamental idea of DP, as well as reinforcement learning in general, is the use of state values and actions to look for good policies.

Getting ready

In this recipe, we will address...

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