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TensorFlow 2 Reinforcement Learning Cookbook

gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch. What you will learn Build;

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Reinforcement Learning From Scratch

spectacular reinforcement learning algorithms work? With easy-to-understand explanations and clear examples in Java and Greenfoot, you can;

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Hands-On Reinforcement Learning with Python

learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you;

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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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Hands-On Reinforcement Learning for Games

Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and;

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Python Reinforcement Learning

Learning Path includes content from the following Packt products: Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran Python;

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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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Statistical Reinforcement Learning

of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches, including model-based and;

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Statistical Reinforcement Learning

of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches, including model-based and;

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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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Algorithms for Reinforcement Learning

that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given;

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Algorithms for Reinforcement Learning

that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given;

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Reinforcement Learning

discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. Reinforcement learning;

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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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Motivated Reinforcement Learning

extend reinforcement learning to adaptive, multitask learning in complex, dynamic environments - the goal being to understand how machines can;

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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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Reinforcement Learning Algorithms with Python

learning from scratch, this book is for you. You'll also find this reinforcement learning book useful if you want to learn about the advancements;

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Supervised Reinforcement Learning

Supervised Reinforcement Learning is een boek van Karla Conn;

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Agile Visualization with Pharo

learning (Q-Learning, from scratch) and use visualizations to monitor learning and state exploration Use GitHub Action to generate software;

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Reinforcement Learning

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational;

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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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Human-Robot Interaction Control Using Reinforcemen t Learning

, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control;

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Java Deep Learning Cookbook

Deeplearning4j to implement deep learning models from scratch Explore recipes for developing, training, and fine-tuning your neural network models;

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The Self-Learning Blueprint

An approach to instantly make sense of a topic when learning from scratch and teaching yourself.;

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Hands-On Intelligent Agents with OpenAI Gym

algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing;

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Deep Reinforcement Learning

world's leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the;

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