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吴恩达教授的机器学习讲义，非常详细的公式推导

内容简介, 自然语言处理是运用计算机对自然语言进行分析和理解，从而使计算机在某种程度上具有人的语言能力。《自然语言处理》重点介绍了自然语言处理的基本问题、相关方法和重要领域，包括汉语句型分析与分布统计、语料库处理、文本自动分类与检索、文本自动文摘、中文文本自动校对、人机交互技术、汉语盲文翻译和甲骨文信息处理等。《自然语言处理》既有数学理论模型，又有实验论证，从理论到实践，深入浅出，结构合理，概念阐述明确，公式推导简明，易于理解，便于教学。《自然语言处理》可作为中文信息处理专业和计算语言学专业的高年级本科生、研究生的教材或参考书，也可供自然语言处理或计算机信息处理和人工智能领域的相关人员参考。, -------, 目录, 第1章 论, 1.1 自然语言处理研究的意义、历史与现状, 1.2 自然语言处理研究的方法、特点和规律, 本章参考文献, 第2章 然语言处理的基本问题, 2.1 汉语自动分词, 2.2 汉语文本自动标注, 2.3 句法分析, 2.4 语料库处理, 本章参考文献, 第3章 语句型分析与分布统计, 3.1 句型分析与句型分布统计的意义, 3.2 句型分析的理论基础和策略, 3.3 句型成分分析中的几个问题, 3.4 句型分析与句型匹配统计的算法实现, 本章参考文献, 第4章 本自动分类与检索, 4.1 引言, 4.2 常用的分类及检索模型介绍, 4.3 粗集理论在分类与检索中的应用, 4.4 自然语言处理通用模块的设计与实现, 4.5 基于粗集理论的自动分类及检索功能的设计与实现, 4.6 模糊分类系统设计的基本思想, 本章参考文献, 第5章 本自动文摘, 5.1 自动文摘概论, 5.2 自动文摘的实现原理, 5.3 中文文摘实验系统, 5.4 基于概念统计的自动文摘方法, 本章参考文献, 第6章 文文本的自动校对, 6.1 引言, 6.2 自动校对的基本技术, 6.3 系统的技术实现, 6.4 词级查错方法, 6.5 语法查错方法, 6.6 语义查错方法, 6.7 实验结果与小结, 本章参考文献, 第7章 机交互技术, 7.1 引言, 7.2 语音识别概况, 7.3 神经网络语音识别研究进展, 7.4 汉语语音理解, 7.5 语音合成与自然语言生成, 7.6 对话系统的发展状况与研究方法, 7.7 对话系统中的句法分析, 7.8 鲁棒的口语分析器, 7.9 对话系统中的语义分析, 7.10对话系统中的话语分析, 7.11系统的实现及评测, 本章参考文献, 第8章 然语言处理应用, 8.1 汉语盲文翻译, 8.2 甲骨文信息处理, 本章参考文献, 中英文名词对照表, 后记

'Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.' -- Elon Musk, co-chair of OpenAI; co-founder and CEO of Tesla and SpaceX, Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning., The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models., Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

The Core Series is designed to provide you – the experienced programmer – with the essential information you need to quickly learn and apply the latest, most important technologies. Authors in The Core Series are seasoned professionals who have pioneered the use of these technologies to achieve tangible results in real-world settings. These experts: • Share their practical experiences • Support their instruction with real-world examples • Provide an accelerated, highly effective path to learning the subject at hand The resulting book is a no-nonsense tutorial and thorough reference that allows you to quickly produce robust, production-quality code.

With the approachment of Big Data,for fixing some limitations of Hadoop's properties, Spark appears and will bring another revolution!

该书以机器学习与计算统计为主题背景，专门讲述如何挖掘和分析Web上的数据和资源，如何分析用户体验，市场营销，个人品味等诸多信息，并得出有用的结论，通过复杂的算法来从Web网站获取、手机并分析用户的数据和反馈信息，以便创造新的用户价值和商业价值

遗传神经算法结合的图像编码是一种有损编码，但是在传统的BP神经网络中要有很多的先进之处，经恢复的图像效果更佳

实现了基本的内容发布和内容栏目修改等后台管理与前台显示

多媒体播放器开发，里面代码运行过了，非常好用

挺不错的管理模板，对于jsp编程的同学非常有用的