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Reinforcement Learning for Finance

library. Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN - two;

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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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Machine Learning for Finance

A guide to advances in machine learning for financial professionals, with working Python code Key Features Explore advances in machine;

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Reinforcement Learning

concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement;

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Machine Learning in Finance

computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for;

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Machine Learning in Finance

computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for;

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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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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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Machine Learning and Data Science Blueprints for Finance From Building Trading Strategies to RoboAdvisors Using Python

over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for;

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Human-Robot Interaction Control Using Reinforcemen t Learning

identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical;

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Statistical Reinforcement Learning

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic;

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Statistical Reinforcement Learning

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic;

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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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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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Reinforcement and Systemic Machine Learning for Decision Making

Reinforcement and Systemic Machine Learning for Decision Making explores a newer and growing avenue of machine learning algorithm in the;

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Motivated Reinforcement Learning

learning. The authors start with overviews of motivation and reinforcement learning, then describe models for motivated reinforcement learning. The;

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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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Algorithms for Reinforcement Learning

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure;

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Algorithms for Reinforcement Learning

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure;

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Zai:Deep Reinforcement Learning i_p

of its past decisions, and uses this information to optimize its behavior for maximum long-term return. Deep reinforcement learning famously;

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Supervised Reinforcement Learning

Supervised Reinforcement Learning is een boek van Karla Conn;

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Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context

This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios;

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Reinforcement Learning Algorithms

is intended for reinforcement learning students and researchers with a firm grasp of linear algebra, statistics, and optimization. Nevertheless, all;

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Python Reinforcement Learning Projects

using TensorFlow for RL Use RL algorithms in Python and TensorFlow to solve CartPole balancing Create deep reinforcement learning algorithms to;

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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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Reinforcement Learning

of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part;

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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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