Hands-On Reinforcement Learning with Python
Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.
Offered by
Difficulty Level
Intermediate
Completion Time
10h36m
Language
English
About Book
Who Is This Book For?
If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book.
Hands-On Reinforcement Learning with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h36m total length
Introduction to Reinforcement Learning
Getting started with OpenAI and Tensorflow
Markov Decision process and Dynamic Programming
Gaming with Monte Carlo Tree Search
Temporal Difference Learning
Multi-Armed Bandit Problem
Deep Learning Fundamentals
Deep Learning and Reinforcement
Playing Doom With Deep Recurrent Q Network
Asynchronous Advantage Actor Critic Network
Policy Gradients and Optimization
Capstone Project – Car Racing using DQN
Current Research and Next Steps
Related Resources
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