Hands-On Q-Learning with Python
Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.
Offered by
Difficulty Level
Intermediate
Completion Time
7h4m
Language
English
About Book
Who Is This Book For?
If you are a machine learning developer, engineer, or professional who wants to explore the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.
Hands-On Q-Learning with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 7h4m total length
Brushing Up on Reinforcement Learning Concepts
Getting Started with the Q-Learning Algorithm
Setting Up Your First Environment with OpenAI Gym
Teaching a Smartcab to Drive Using Q-Learning
Building Q-Networks with TensorFlow
Digging Deeper into Deep Q-Networks with Keras and TensorFlow
Decoupling Exploration and Exploitation in Multi-Armed Bandits
Further Q-Learning Research and Future Projects
Assessments
Related Resources
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