“tag:coursera”
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算法(第4版) [图书] 豆瓣
Algorithms (4/e)
9.5 (24 个评分) 作者: [美] Robert Sedgewick / [美] Kevin Wayne 译者: 谢路云 人民邮电出版社 2012 - 10
本书全面讲述算法和数据结构的必备知识,具有以下几大特色。
 算法领域的经典参考书
Sedgewick畅销著作的最新版,反映了经过几十年演化而成的算法核心知识体系
 内容全面
全面论述排序、搜索、图处理和字符串处理的算法和数据结构,涵盖每位程序员应知应会的50种算法
 全新修订的代码
全新的Java实现代码,采用模块化的编程风格,所有代码均可供读者使用
 与实际应用相结合
在重要的科学、工程和商业应用环境下探讨算法,给出了算法的实际代码,而非同类著作常用的伪代码
 富于智力趣味性
简明扼要的内容,用丰富的视觉元素展示的示例,精心设计的代码,详尽的历史和科学背景知识,各种难度的练习,这一切都将使读者手不释卷
 科学的方法
用合适的数学模型精确地讨论算法性能,这些模型是在真实环境中得到验证的
 与网络相结合
配套网站algs4.cs.princeton.edu提供了本书内容的摘要及相关的代码、测试数据、编程练习、教学课件等资源
社交网站的数据挖掘与分析 [图书] 豆瓣
Mining the Social Web : Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
作者: Matthew A·Russell 译者: 师蓉 机械工业出版社 2012 - 2
Facebook、Twitter和LinkedIn产生了大量宝贵的社交数据,但是你怎样才能找出谁通过社交媒介正在进行联系?他们在讨论些什么?或者他们在哪儿?这本简洁而且具有可操作性的书将揭示如何回答这些问题甚至更多的问题。你将学到如何组合社交网络数据、分析技术,如何通过可视化帮助你找到你一直在社交世界中寻找的内容,以及你闻所未闻的有用信息。
每个独立的章节介绍了在社交网络的不同领域挖掘数据的技术,这些领域包括博客和电子邮件。你所需要具备的就是一定的编程经验和学习基本的Python工具的意愿。
•获得对社交网络世界的直观认识
•使用GitHub上灵活的脚本来获取从诸如Twitter、Facebook和LinkedIn之类的社交网络API中的数据
•学习如何应用便捷的Python工具来交叉分析你所收集的数据
•通过XHTML朋友圈探讨基于微格式的社交联系
•应用诸如TF-IDF、余弦相似性、搭配分析、文档摘要、派系检测之类的先进挖掘技术
•通过基于HTML5和JavaScript工具包的网络技术建立交互式可视化
Social and Economic Networks [图书] 豆瓣 Goodreads
Social and Economic Networks
作者: Matthew O. Jackson Princeton University Press 2008 - 9
Review
Lucid and comprehensive, Jackson's book elegantly synthesizes several important strands of network science from sociology, physics, mathematics, computer science, and economics. It will be an immensely useful reference for researchers and students alike.
(Duncan Watts, Columbia University )
Product Description
Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function.
This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.
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