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边云智能数据分析与应用 版权信息
- ISBN：9787121460425
- 条形码：9787121460425 ; 978-7-121-46042-5
- 装帧：平塑
- 册数：暂无
- 重量：暂无
- 所属分类：>>
边云智能数据分析与应用 内容简介
随着“十四五”规划纲要中提出“协同发展云服务与边缘计算服务”的观点，边云智能已成为未来发展的重要趋势。本书依托于政策大背景，旨在向读者介绍边云智能的基础知识和应用。书中分为四个篇章，**篇章介绍了边云架构的骨架和基础概念，第二篇章介绍了人工智能算法和深度学习模型，第三篇章介绍了云端决策算法和边缘端轻量化算法，第四篇章介绍了边云智能在智慧教育领域的应用。本书可以使读者了解边云计算的基本概念和原理逻辑，熟悉基本的人工智能计算方法和数据分析的逻辑和运用场景。通过数据科学的思路和方法，读者可以将无人系统的数据智能化应用提升，并培养数据导向思维方式，为未来学习智能无人系统科学与技术学科打下基础。 本书目标明确，技术优选，强调课程思政和润物无声的教育理念，旨在提高学生的数据科学素养和“用数据”的能力。本书面向智能无人系统科学与技术专业的研究生，涵盖人工智能、大数据分析、数据挖掘和边云计算等学科，具有交叉性的特点。同时，资深从业者也可将其作为参考书籍。
边云智能数据分析与应用 目录
第 1 章 绪论 ····························································································1
1.1 边云智能产生的大背景····································································1
1.1.1 新一代信息技术的快速发展·····················································2
1.1.2 国家政策的支持与引导···························································6
1.2 边云智能······················································································7
1.3 边云智能的发展·············································································9
1.3.1 边云智能的三大发展阶段························································9
1.3.2 城市大脑··········································································.11
1.4 “智能 ”新潮头··········································································.13
1.4.1 “智能 ”技术新融合···························································.13
1.4.2 多维度场景应用·································································.14
本章习题··························································································.15
第 2 章 边云架构 ···················································································.16
2.1 系统工程方法论··········································································.17
2.1.1 概述 ················································································.17
2.1.2 基本方法··········································································.17
2.2 边云智能体系架构模型·································································.20
2.2.1 概念框架··········································································.20
2.2.2 层次结构··········································································.22
2.3 协同模式···················································································.23
2.3.1 “云-边”协同 ····································································.24
2.3.2 “边-边”协同 ····································································.25
2.3.3 “边-端”协同 ····································································.27
2.3.4 “云-边-端”协同 ································································.28
2.3.5 度量指标··········································································.28
2.4 边云智能架构应用·······································································.30
2.4.1 “云-边-端”区块链 ·····························································.30
2.4.2 “云-边-端”一体化机器人系统 ··············································.32
本章习题··························································································.33
第 3 章 深度学习 ···················································································.35
3.1 深度学习概念·············································································.36
3.1.1 人工智能与机器学习···························································.36
3.1.2 深度学习··········································································.37
3.1.3 神经网络··········································································.39
3.2 前馈神经网络·············································································.39
3.2.1 感知机模型·······································································.39
3.2.2 反向传播··········································································.42
3.2.3 卷积神经网络····································································.44
3.2.4 几种典型的卷积神经网络·····················································.47
3.3 反馈神经网络·············································································.50
3.3.1 循环神经网络····································································.50
3.3.2 长短期神经网络·································································.53
3.4 Transformer 神经网络 ···································································.56
3.4.1 编码器单元与解码器单元·····················································.58
3.4.2 多头注意力机制·································································.59
3.4.3 非参位置编码····································································.60
本章习题··························································································.61
第 4 章 自然语言处理 ··············
1.1 边云智能产生的大背景····································································1
1.1.1 新一代信息技术的快速发展·····················································2
1.1.2 国家政策的支持与引导···························································6
1.2 边云智能······················································································7
1.3 边云智能的发展·············································································9
1.3.1 边云智能的三大发展阶段························································9
1.3.2 城市大脑··········································································.11
1.4 “智能 ”新潮头··········································································.13
1.4.1 “智能 ”技术新融合···························································.13
1.4.2 多维度场景应用·································································.14
本章习题··························································································.15
第 2 章 边云架构 ···················································································.16
2.1 系统工程方法论··········································································.17
2.1.1 概述 ················································································.17
2.1.2 基本方法··········································································.17
2.2 边云智能体系架构模型·································································.20
2.2.1 概念框架··········································································.20
2.2.2 层次结构··········································································.22
2.3 协同模式···················································································.23
2.3.1 “云-边”协同 ····································································.24
2.3.2 “边-边”协同 ····································································.25
2.3.3 “边-端”协同 ····································································.27
2.3.4 “云-边-端”协同 ································································.28
2.3.5 度量指标··········································································.28
2.4 边云智能架构应用·······································································.30
2.4.1 “云-边-端”区块链 ·····························································.30
2.4.2 “云-边-端”一体化机器人系统 ··············································.32
本章习题··························································································.33
第 3 章 深度学习 ···················································································.35
3.1 深度学习概念·············································································.36
3.1.1 人工智能与机器学习···························································.36
3.1.2 深度学习··········································································.37
3.1.3 神经网络··········································································.39
3.2 前馈神经网络·············································································.39
3.2.1 感知机模型·······································································.39
3.2.2 反向传播··········································································.42
3.2.3 卷积神经网络····································································.44
3.2.4 几种典型的卷积神经网络·····················································.47
3.3 反馈神经网络·············································································.50
3.3.1 循环神经网络····································································.50
3.3.2 长短期神经网络·································································.53
3.4 Transformer 神经网络 ···································································.56
3.4.1 编码器单元与解码器单元·····················································.58
3.4.2 多头注意力机制·································································.59
3.4.3 非参位置编码····································································.60
本章习题··························································································.61
第 4 章 自然语言处理 ··············
展开全部
边云智能数据分析与应用 作者简介
沈钧戈，西北工业大学助理教授，陕西省电子学会图形图象专委会委员，主讲课程为智慧城市与计算机视觉，并负责相关慕课建设。
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