Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it ...
深度学习基础(影印版) [ Fundamentals of Deep Learning] pdf epub mobi txt 电子书 下载 具体描述 内容简介 Google、微软和Facebook等公司正在积极发展内部的深度学习团队。对于我们而言,深度学习仍然是一门非常复杂和难以掌握的课题。如果你熟悉Python,并且具有微积分背景,以及对于机器学习的基本理解,本书将帮助你开启...
deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started. Table of Contents...
This text then considers the processes of acquisition, including a detailed discussion of contiguity, practice, and reinforcement. Other chapters include an extensive discussion of issues, problems, and alternative theories within the field of retention. This book discusses as well the problem of ...
Recently, deep learning has achieved great success in visual tracking tasks, particularly in single-object tracking. This paper provides a comprehensive review of state-of-the-art single-object tracking algorithms based on deep learning. First, we introduce basic knowledge of deep visual tracking, in...
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By the end of this exam guide, you’ll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources. Who is this book for? Whether you're a cloud engineer, software developer, an aspiring data scientist, or simply interested in learning AI...
For example, owing to the challenges of establishing a direct driving model and nonlinear interference in practical experimental environments, reinforcement learning has been conducted using a lot of experimental motion prediction data, resulting in desirable control outcomes. In addition to the creation ...
According to learning style, machine learning algorithms can be generally classified into three types: supervised learning, unsupervised learning, and reinforcement learning, as shown in Table 9. Owing to its accuracy and efficiency, supervised learning is commonly used in energy-related fields [221],...