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Foundations of Deep Reinforcement Learning

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL;

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Deep Reinforcement Learning with Python

Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics;

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TensorFlow for Deep Learning From Linear Regression to Reinforcement Learning

convolutional neural networks Handle natural language datasets with recurrent neural networks Use reinforcement learning to solve games such as tic;

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Grokking Deep Reinforcement Learning

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required;

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TensorFlow 2 Reinforcement Learning Cookbook

Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key;

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Hands-On Deep Learning for Games

Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key Features Apply the;

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Reinforcement Learning

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve;

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Reinforcement Learning for Finance

This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the TensorFlow;

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Zai:Deep Reinforcement Learning i_p

cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along;

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Hands-On Reinforcement Learning with Python

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the;

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Practical MATLAB Deep Learning

deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to;

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Practical MATLAB Deep Learning

deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to;

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Reinforcement Learning for Cyber-Physical Systems

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields;

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Reinforcement Learning for Cyber-Physical Systems

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields;

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Python Reinforcement Learning Projects

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key Features Implement Q-learning;

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Reinforcement Learning

Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their;

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Deep Reinforcement Learning

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Deep Reinforcement Learning

Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as;

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The The Reinforcement Learning Workshop

Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and;

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Applied Reinforcement Learning with Python

Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important;

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Fundamentals Of Deep Learning

dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning;

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Deep Learning and Practice with MindSpore

(CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud;

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Deep Learning and Practice with MindSpore

(CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud;

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Deep Reinforcement Learning Hands-On

New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised and;

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Python Reinforcement Learning

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features Your entry;

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Introduction to Machine Learning

, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing;

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PyTorch Deep Learning Hands-On

Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and more Build deep learning workflows and take deep;

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