Book Image

Python Machine Learning By Example - Third Edition

By : Yuxi (Hayden) Liu
Book Image

Python Machine Learning By Example - Third Edition

By: Yuxi (Hayden) Liu

Overview of this book

Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting with sequences using recurring neural networks, and leveraging reinforcement learning for making decisions, the book has been considerably updated for the latest enterprise requirements. At the same time, this book provides actionable insights on the key fundamentals of ML with Python programming. Hayden applies his expertise to demonstrate implementations of algorithms in Python, both from scratch and with libraries. Each chapter walks through an industry-adopted application. With the help of realistic examples, you will gain an understanding of the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. By the end of this ML Python book, you will have gained a broad picture of the ML ecosystem and will be well-versed in the best practices of applying ML techniques to solve problems.
Table of Contents (17 chapters)
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Solving the Taxi problem with the Q-learning algorithm

Q-learning is also a model-free learning algorithm. It updates the Q-function for every step in an episode. We will demonstrate how Q-learning is used to solve the Taxi environment. It is a typical environment with relatively long episodes. So let's first simulate the Taxi environment.

Simulating the Taxi environment

In the Taxi environment ( the agent acts as a taxi driver to pick up the passenger from one location and drop off the passenger at the destination.

All subjects are on a 5 * 5 grid. Take a look at the following example:

Figure 14.6: Example of the Taxi environment

Tiles in certain colors have the following meanings:

  • Yellow: The location of the empty taxi (without the passenger)
  • Blue: The passenger's location
  • Purple: The passenger's destination
  • Green: The location of the taxi with the passenger

The starting...