深度学习原理与TensorFlow实践

图书标准信息

• 作者 闭应洲
• 出版社 电子工业出版社
• 出版时间 2022-08
• 版次 1
• ISBN 9787121441592
• 定价 54.00元
• 装帧 其他
• 开本 16开
• 页数 276页

【内容简介】

本书采用“理论 +实践”的方式，全面系统地讲授了深度学习的基本原理以及使用 TensorFlow实现各类深度学习网络的方法。全书共 10章，第 1～3章主要介绍深度学习的基础知识，包括深度学习的概念和应用、深层神经网络的训练和优化、 TensorFlow的内涵和特点等内容；第 4～5章主要介绍 TensorFlow的安装，以及计算模型、数据模型、运行模型等 TensorFlow编程的基础知识；第 6～10章主要围绕 TensorFlow介绍各类深度学习网络，包括单个神经元、多层神经网络、卷积神经网络、循环神经网络、深度学习网络进阶等。全书在各个章节设置有大量的实验和实操案例，兼具知识性和实用性。

【作者简介】

闭应洲，南宁师范大学教授，主要研究方向为智能计算、智能医学图像处理及社会计算。主持和参与了10多项科研项目的研究工作，发布论文50多篇。2012年2月至2013年2月在美国亚利桑那州立大学访学，重点研究从海量数据中获取知识所必需的理论和技术。

【目录】

目 录

第 1章引言····················································································································1 

1.1 人工智能简介······································································································1 

1.2 机器学习简介······································································································2 

1.2.1 机器学习的概念·····························································································2 

1.2.2 机器学习的本质·····························································································2 

1.2.3 机器学习的步骤·····························································································3 

1.2.4 机器学习的关键点··························································································5 

1.2.5 机器学习的实战·····························································································6 

1.2.6 机器学习的教材·····························································································7 

1.3 机器学习的分类 ··································································································8 

1.3.1 有监督学习···································································································8 

1.3.2 无监督学习···································································································9 

1.3.3 半监督学习································································································.10 

1.3.4 强化学习···································································································.11 

1.4 本章小结··········································································································.12

第 2章深度学习的原理 ·······························································································.13 

2.1 深度学习简介···································································································.13 

2.1.1 深度学习的概念··························································································.13 

2.1.2 深度学习的特点··························································································.13 

2.2 深度学习的现实意义 ························································································.14 

2.2.1 多层神经网络的模型结构 ··············································································.14 

2.2.2 非线性处理能力··························································································.14 

2.2.3 特征自动提取和转换····················································································.16 

2.3 深度学习的应用领域 ························································································.16 

2.3.1 计算机视觉································································································.17 

2.3.2 自然语言处理·····························································································.20 

2.3.3 语音识别···································································································.21 

2.4 深层神经网络简介····························································································.22 

2.4.1 神经元模型································································································.22 

2.4.2 单层神经网络·····························································································.23 

2.4.3 深层神经网络·····························································································.24 

2.4.4 深层神经网络节点·······················································································.24 

2.4.5 深层神经网络参数·······················································································.25 

2.4.6 节点输出值计算··························································································.25 

2.5 深层神经网络的训练与优化 ··············································································.26 

2.5.1 深层神经网络的训练····················································································.26 

2.5.2 深层神经网络的优化····················································································.32 

2.6 本章小结·····························