Illustrated Deep Learning

An intuitive introduction to processing natural language data with TensorFlow-Keras deep learning models.

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.

Artificial intelligence (AI) applications bring agility and modernity to our lives, and the reinforcement learning technique is at the forefront of this technology. It can outperform human competitors in strategy games, creative compositing, and autonomous movement. Moreover, it is just starting to transform our civilization.

This book provides an introduction to AI, specifies machine learning techniques, and explores various aspects of reinforcement learning, approaching the latest concepts in a didactic and illustrated manner. It is aimed at students who want to be part of technological advances and professors engaged in the development of innovative applications, helping with academic and industrial challenges.

Understanding the Fundamentals of Reinforcement Learning will allow you to:

Understand essential AI concepts
Gain professional experience
Interpret sequential decision problems and solve them with reinforcement learning
Learn how the Q-Learning algorithm works
Practice with commented Python code
Find advantageous directions