图书标签: 数据挖掘 机器学习 Data-Mining 计算机 计算机科学 互联网 个性化推荐 信息检索
发表于2025-02-08
Data Mining pdf epub mobi txt 电子书 下载 2025
The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges.
* Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Jiawei Han(韩家炜),是伊利诺伊大学厄巴纳-尚佩恩分校计算机科学系的Bliss教授。他因知识发现和数据挖掘研究方面的贡献而获得许多奖励,包括ACM SIGKDD创新奖(2004)、IEEE计算机学会技术成就奖(2005)和IEEE W.Wallace McDowell奖(2009)。他是ACM和IEEE会士。他还担任《ACM Transactions on Knowledge Discovery from Data》的执行主编(2006—2011)和许多杂志的编委,包括《IEEE Transactions on Knowledge and Data Engineering》和《Data Mining Knowledge Discovery》。
拥有加拿大康考迪亚大学计算机科学硕士学位,现在加拿大西蒙弗雷泽大学从事博士后研究工作。
粗粗浏览了一遍,了解一些基本概念
评分推荐和Coursera的专项课程一起听。Coursera的Slides给出了书中很多较为简略环节的参考文献,书和课程组合,兼顾基础与引申。在线课程精心准备,游戏化做得非常棒,习题集还搞了个名人堂机制,动力满满啊!论坛也很活跃,负责算法R实现那个TA尤其赞,学到了很多!
评分good textbook, even though i decided not to follow the path towards a trendy so-called data scientist.
评分综合性很强的一本书。可以作为基础学习或者查阅。有一些伪代码,很有启发性但是在大数据时代很多算法的分布式实现还要去看源码,例如mllib, mahout。 对数据仓库,olap server的讲解蛮不错的。毕竟dm和dw的关系很密切。此外,fpgrow算法讲解很到位
评分good textbook, even though i decided not to follow the path towards a trendy so-called data scientist.
大三下时就买了,为了准备一下保研的方向,当时只是粗略的读懂了一点。浙大面试时问了我一个K-Means自己都记不太清了。 研一上的<<数据仓库与数据挖掘>>课程也基本使用了这本教材,然而长期不去上课导致自己好多内容学的并不扎实,最后的考试也考的很烂;现在回想,贝叶...
评分 评分这本书是准备跟随浙江大学的课程学习而购买的课本,里面的知识比较全面。部分比较深入的知识由于课上没有 讲解,因此我也将它跳过了。因为这学期选修了数据挖掘的课,需要一个中文版的课本进行学习,选择这本书还是不错的。 这本书很适合自学,因为是将理论与算法相结合讲解的...
评分讲的很不错,就死实现起来有点麻烦。不知道apriori算法大家怎么实现的?主要是采用什么数据结构存储。
评分大三下时就买了,为了准备一下保研的方向,当时只是粗略的读懂了一点。浙大面试时问了我一个K-Means自己都记不太清了。 研一上的<<数据仓库与数据挖掘>>课程也基本使用了这本教材,然而长期不去上课导致自己好多内容学的并不扎实,最后的考试也考的很烂;现在回想,贝叶...
Data Mining pdf epub mobi txt 电子书 下载 2025