You're reading from Python Machine Learning by Example Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781800209718

Length 526 pages

Edition 3rd Edition

Languages

Python

Tools

PyTorch

Concepts

Machine Learning

Author (1):

Yuxi (Hayden) Liu

View More author details

Table of Contents (17) Chapters

Preface

1. Getting Started with Machine Learning and Python

2. Building a Movie Recommendation Engine with Naïve Bayes FREE CHAPTER

3. Recognizing Faces with Support Vector Machine

4. Predicting Online Ad Click-Through with Tree-Based Algorithms

5. Predicting Online Ad Click-Through with Logistic Regression

6. Scaling Up Prediction to Terabyte Click Logs

7. Predicting Stock Prices with Regression Algorithms

8. Predicting Stock Prices with Artificial Neural Networks

9. Mining the 20 Newsgroups Dataset with Text Analysis Techniques

10. Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

11. Machine Learning Best Practices

12. Categorizing Images of Clothing with Convolutional Neural Networks

13. Making Predictions with Sequences Using Recurrent Neural Networks

14. Making Decisions in Complex Environments with Reinforcement Learning

15. Other Books You May Enjoy

16. Index

Performing Monte Carlo learning

Monte Carlo (MC)-based reinforcement learning is a model-free approach, which means it doesn't need a known transition matrix and reward matrix. In this section, you will learn about MC policy evaluation on the Blackjack environment, and solve the environment with MC Control algorithms. Blackjack is a typical environment with an unknown transition matrix. Let's first simulate the Blackjack environment.

Simulating the Blackjack environment

Blackjack is a popular card game. The game has the following rules:

The player competes against a dealer and wins if the total value of their cards is higher and doesn't exceed 21.
Cards from 2 to 10 have values from 2 to 10.
Cards J, K, and Q have a value of 10.
The value of an ace can be either 1 or 11 (called a "usable" ace).
At the beginning, both parties are given two random cards, but only one of the dealer's cards is revealed to the player...