PyTorch 1.x Reinforcement Learning Cookbook: Over 60 recipes to design, develop, and deploy self-learning AI models using Python
Author:   Yuxi (Hayden) Liu
Publisher:   Packt Publishing Limited
ISBN:  

9781838551964


Pages:   340
Publication Date:   31 October 2019
Format:   Paperback
Availability:   Available To Order   Availability explained
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PyTorch 1.x Reinforcement Learning Cookbook: Over 60 recipes to design, develop, and deploy self-learning AI models using Python


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Author:   Yuxi (Hayden) Liu
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
ISBN:  

9781838551964


ISBN 10:   1838551964
Pages:   340
Publication Date:   31 October 2019
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Table of Contents Getting started with reinforcement learning and PyTorch Markov Decision Process and Dynamic Programming Monte Carlo Methods for making numerical estimations Temporal Difference and Q-Learning Solving Multi Armed Bandit problems Scaling up Learning with Function Approximation Deep Q-Networks in Action Implementing Policy Gradients and Policy Optimization Capstone Project: Playing Flappy Bird with DQN

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Author Information

Yuxi (Hayden) Liu is an experienced data scientist who's focused on developing machine learning and deep learning models and systems. He has worked in a variety of data-driven domains and has applied his expertise in reinforcement learning to computational. He is an education enthusiast and the author of a series of ML books. His first book, Python Machine Learning By Example, was a #1 bestseller on Amazon India in 2017 and 2018. His other books include R Deep Learning Projects and Hands-On Deep Learning Architectures with Python published by Packt. He also published five first-authored IEEE transaction and conference papers during his master's research at the University of Toronto.

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