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Jingdong book

Python神经网络编程

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Python神经网络编程

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当前,深度学习和人工智能的发展和应用给人们留下了深刻的印象。神经网络是深度学习和人工智能的关键元素,然而,真正了解神经网络工作机制的人少之又少。本书用轻松的笔触,一步一步揭示了神经网络的数学思想,并介绍如何使用Python编程语言开发神经网络。

本书将带领您进行一场妙趣横生却又有条不紊的旅行——从一个非常简单的想法开始,逐步理解神经网络的工作机制。您无需任何超出中学范围的数学知识,并且本书还给出易于理解的微积分简介。本书的目标是让尽可能多的普通读者理解神经网络。读者将学习使用Python开发自己的神经网络,训练它识别手写数字,甚至可以与专业的神经网络相媲美。

本书适合想要了解深度学习、人工智能和神经网络的读者阅读,尤其适合想要通过Python编程进行神经网络开发的读者参考。


这是一本精心编写、给完全初学者的图书。它带领读者构建一个真正、有效的神经网络,而不需要读者具备任何复杂的数学知识和深度学习的理论。

——M Ludvig

强烈推荐本书。这本书使得人工神经网络的概念非常清晰而容易理解。读者应该尝试重复本书中给出的示例,以便让本书发挥大的作用。我就是这么做的,效果不错!

——美亚的一位读者

如果你对人工智能或神经网络感兴趣的话,这应该是你的第1本入门书。本书对主题的介绍非常清晰,几乎涉及理解神经网络所需的所有知识,包括微积分、统计、矩阵、编程等等。

——Niyazi Kemer

这是一本优秀的入门图书,它有几个显著特点。它细致而透彻地介绍了神经网络。它用非常精简、实用的方式介绍了数学知识,特别是矩阵乘法和一些简单的微积分,使得读者能够很容易接受一次数学训练。它使用IPython作为计算平台,引导读者使用Python编写神经网络。

——Daniel Oderbolz


Content Description

本书首先从简单的思路着手,详细介绍了理解神经网络如何工作所必须的基础知识。第一部分介绍基本的思路,包括神经网络底层的数学知识,第2部分是实践,介绍了学习Python编程的流行和轻松的方法,从而逐渐使用该语言构建神经网络,以能够识别人类手写的字母,特别是让其像专家所开发的网络那样地工作。第3部分是扩展,介绍如何将神经网络的性能提升到工业应用的层级,甚至让其在Raspberry Pi上工作。

Author Description

塔里克·拉希德 拥有物理学学士学位、机器学习和数据挖掘硕士学位。他常年活跃于伦敦的技术领域,领导并组织伦敦Python聚会小组(近3000名成员)。


Catalogue

第 1 章神经网络如何工作001

1.1尺有所短,寸有所长 001

1.2一台简单的预测机 003

1.3分类器与预测器并无太大差别008

1.4训练简单的分类器011

1.5有时候一个分类器不足以求解问题020

1.6神经元——大自然的计算机器024

1.7在神经网络中追踪信号033

1.8凭心而论,矩阵乘法大有用途037

1.9使用矩阵乘法的三层神经网络示例043

1.10学习来自多个节点的权重051

1.11多个输出节点反向传播误差053

1.12反向传播误差到更多层中054

1.13使用矩阵乘法进行反向传播误差058

1.14我们实际上如何更新权重061

1.15权重更新成功范例077

1.16准备数据078


第 2 章使用Python进行DIY 083

2.1Python083

2.2交互式Python = IPython084

2.3优雅地开始使用Python085

2.4使用Python制作神经网络 105

2.5手写数字的数据集MNIST 121


第 3 章趣味盎然 153

3.1自己的手写数字153

3.2神经网络大脑内部156

3.3创建新的训练数据:旋转图像160

3.4结语164


附录A微积分简介 165

A.1一条平直的线166

A.2一条斜线168

A.3一条曲线170

A.4手绘微积分172

A.5非手绘微积分174

A.6无需绘制图表的微积分177

A.7模式180

A.8函数的函数182


附录B使用树莓派来工作 186

B.1安装IPython187

B.2确保各项工作正常进行193

B.3训练和测试神经网络194

B.4树莓派成功了 195


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Brand Jingdong book
Brand Origin China

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