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Deep Reinforcement Learning with Python

, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding;

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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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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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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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TensorFlow 2 Reinforcement Learning Cookbook

intelligence applications. Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers;

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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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PyTorch Deep Learning Hands-On

reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient;

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Handbook of Reinforcement Learning and Control

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory;

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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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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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Advanced Deep Learning with Keras

, GANs, VAEs, and deep reinforcement learning that drive today's most impressive AI results. Key Features Explore the most advanced deep;

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Applied Reinforcement Learning with Python

Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them;

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Python Reinforcement Learning Projects

even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each;

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Practical MATLAB Deep Learning

with examples Use MATLAB toolboxes related to deep learning Implement tokamak disruption prediction Now includes reinforcement learning;

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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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An Introduction to Machine Learning

models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and;

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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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Python Deep Learning

computer vision and NLP Learn how a computer can navigate in complex environments with reinforcement learning Book DescriptionWith the surge;

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Hands-On Deep Learning with R

with using reinforcement learning and deep reinforcement learning to solve various real-world problems. By the end of this deep learning book;

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Deep 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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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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Deep Reinforcement Learning Hands-On

edition of the bestselling introduction to deep reinforcement learning, expanded with six new chapters Learn advanced exploration techniques;

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Deep Reinforcement Learning

can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are;

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Hands-On Deep Learning for Games

. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and;

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Python Reinforcement Learning

learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by;

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