深度学习原理与应用实践

本书特色

[

本书全面、系统地介绍深度学习相关的技术，包括人工神经网络，卷积神经网络，深度学习平台及源代码分析，深度学习入门与进阶，深度学习高级实践，所有章节均附有源程序，所有实验读者均可重现，具有高度的可操作性和实用性。通过学习本书，研究人员、深度学习爱好者，能够在3 个月内，系统掌握深度学习相关的理论和技术。

]

内容简介

[

本书全面、系统地介绍深度学习相关的技术，所有章节均附有源程序，所有实验读者均可重现，具有高度的可操作性和实用性。

]

作者简介

[

　　　　张重生，博士，教授，硕士生导师，河南大学大数据研究中心、大数据团队带头人。研究领域为大数据分析、深度学习、数据挖掘、数据库、数据流（实时数据分析）。
　　　　博士毕业于 INRIA,France(法国国家信息与自动化研究所)，获得优秀博士论文荣誉。2010年08月至2011年3月，在美国加州大学洛杉矶分校(UCLA)，计算机系，师从著名的数据库专家Carlo Zaniolo教授，从事数据挖掘领域的合作研究。 2012-2013,挪威科技大学，ERCIM/Marie-Curie Fellow。

]

目录

目 录深度学习基础篇第1 章 绪论 ·································································································· 21.1 引言 ······································································································· 21.1.1 Google 的深度学习成果 ···························································· 21.1.2 Microsoft 的深度学习成果························································· 31.1.3 国内公司的深度学习成果 ························································· 31.2 深度学习技术的发展历程 ···································································· 41.3 深度学习的应用领域 ············································································ 61.3.1 图像识别领域 ············································································· 61.3.2 语音识别领域 ············································································· 61.3.3 自然语言理解领域 ····································································· 71.4 如何开展深度学习的研究和应用开发 ················································· 7本章参考文献 ······························································································ 11第2 章 国内外深度学习技术研发现状及其产业化趋势 ······························· 132.1 Google 在深度学习领域的研发现状 ·················································· 132.1.1 深度学习在Google 的应用 ······················································ 132.1.2 Google 的TensorFlow 深度学习平台 ······································ 142.1.3 Google 的深度学习芯片TPU ·················································· 152.2 Facebook 在深度学习领域的研发现状 ·············································· 152.2.1 Torchnet ···················································································· 152.2.2 DeepText ··················································································· 162.3 百度在深度学习领域的研发现状 ······················································· 172.3.1 光学字符识别 ··········································································· 172.3.2 商品图像搜索 ··········································································· 172.3.3 在线广告 ·················································································· 182.3.4 以图搜图 ·················································································· 182.3.5 语音识别 ·················································································· 182.3.6 百度开源深度学习平台MXNet 及其改进的深度语音识别系统Warp-CTC ····· 192.4 阿里巴巴在深度学习领域的研发现状 ··············································· 192.4.1 拍立淘 ······················································································ 192.4.2 阿里小蜜——智能客服Messenger ········································· 202.5 京东在深度学习领域的研发现状 ······················································· 202.6 腾讯在深度学习领域的研发现状 ······················································· 212.7 科创型公司（基于深度学习的人脸识别系统） ······························· 222.8 深度学习的硬件支撑——NVIDIA GPU ············································ 23本章参考文献 ······························································································ 24深度学习理论篇第3 章 神经网络 ························································································· 303.1 神经元的概念 ······················································································ 303.2 神经网络 ····························································································· 313.2.1 后向传播算法 ··········································································· 323.2.2 后向传播算法推导 ··································································· 333.3 神经网络算法示例 ·············································································· 36本章参考文献 ······························································································ 38第4 章 卷积神经网络 ················································································· 394.1 卷积神经网络特性 ················································································ 394.1.1 局部连接 ·················································································· 404.1.2 权值共享 ·················································································· 414.1.3 空间相关下采样 ······································································· 424.2 卷积神经网络操作 ·················4

封面

书名:深度学习原理与应用实践

作者:张重生

页数:232

定价:¥48.0

出版社:电子工业出版社

出版日期:暂无

ISBN:9787121304132

PDF电子书大小:157MB 高清扫描完整版