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Python数据分析与挖掘实战
Matthew A. Russell
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社交网站数据如同深埋地下的“金矿”,如何利用这些数据来发现哪些人正通过社交媒介进行联系?他们正在谈论什么?或者他们在哪儿?本书第2版对上一版内容进行了全面更新和修订,它将揭示回答这些问题的方法与技巧。你将学到如何获取、分析和汇总散落于社交网站(包括Facebook、Twitter、LinkedIn、Google+、 GitHub、邮件、网站和博客等)的数据,以及如何通过可视化找到你一直在社交世界中寻找的内容和你闻所未闻的有用信息。
■ 借助IPython Notebook、自然语言工具包、NetworkX和其他科学计算工具挖掘主流社交网站
■ 使用高级文本挖掘技术(如聚类和TF-IDF)来提取人类语言数据中有价值的知识
■ 通过发现GitHub上人、编程语言和代码工程间的亲密性,构建兴趣图谱
■ 利用D3.js进行交互式可视化,充分发挥HTML5和JavaScript工具包的灵活特性
■ 以“问题-解决方案-讨论”的方式详细讲解深入挖掘Twitter数据的实用技术,并提供代码示例
本书的配套代码在公开的GitHub代码库中进行维护,可以通过一站式虚拟机来访问,你只需要使用方便易用的IPython Notebook,即可进入愉快的交互式学习情景。
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Published February 1, 2015
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Matthew A. Russell
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