You're reading from Python Machine Learning By Example Unlock machine learning best practices with real-world use cases

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781835085622

Length 518 pages

Edition 4th Edition

Languages

Python

Tools

PyTorch

Concepts

Computer Vision

Author (1):

Yuxi (Hayden) Liu

View More author details

Table of Contents (18) Chapters

Preface

1. Getting Started with Machine Learning and Python

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

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

4. Predicting Online Ad Click-Through with Logistic Regression

5. Predicting Stock Prices with Regression Algorithms

6. Predicting Stock Prices with Artificial Neural Networks

7. Mining the 20 Newsgroups Dataset with Text Analysis Techniques

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

9. Recognizing Faces with Support Vector Machine

10. Machine Learning Best Practices

11. Categorizing Images of Clothing with Convolutional Neural Networks

12. Making Predictions with Sequences Using Recurrent Neural Networks

13. Advancing Language Understanding and Generation with the Transformer Models

14. Building an Image Search Engine Using CLIP: a Multimodal Approach

15. Making Decisions in Complex Environments with Reinforcement Learning

16. Other Books You May Enjoy

17. 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 Gymnasium’s 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 than the dealer’s 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...