圖書標籤: 數據挖掘 計算機 機器學習 Data Coursera CS 數據分析 軟件工程
发表于2024-12-23
Mining of Massive Datasets pdf epub mobi txt 電子書 下載 2024
Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.
Jure Leskovec is Assistant Professor of Computer Science at Stanford University. His research focuses on mining large social and information networks. Problems he investigates are motivated by large scale data, the Web and on-line media. This research has won several awards including a Microsoft Research Faculty Fellowship, the Alfred P. Sloan Fellowship, Okawa Foundation Fellowship, and numerous best paper awards. His research has also been featured in popular press outlets such as the New York Times, the Wall Street Journal, the Washington Post, MIT Technology Review, NBC, BBC, CBC and Wired. Leskovec has also authored the Stanford Network Analysis Platform (SNAP, http://snap.stanford.edu), a general purpose network analysis and graph mining library that easily scales to massive networks with hundreds of millions of nodes and billions of edges. You can follow him on Twitter at @jure.
bug非常之多, 還找不到地方提交, 讀起來極度痛苦, 前看後忘, 也許裏麵的算法本質上就是這樣, bottom line至少近15年最新的論文成果被這麼串講一下, 本科生也能看懂
評分花費6個月時間,斷斷續續看完,哈希和近似的想法真是開闊瞭眼界。第一迴看比較急促,此書值得反復看,多實踐。
評分花費6個月時間,斷斷續續看完,哈希和近似的想法真是開闊瞭眼界。第一迴看比較急促,此書值得反復看,多實踐。
評分內容不錯,但作為技術嚮的書有些浮於錶麵。
評分勉強一刷吧。到時配閤斯坦福的課再過一遍~
当今时代大规模数据爆炸的速度是惊人的,当然,其应用也是越来越广泛的,从传统的零售业到复杂的商业世界,到处都能见到它的身影。那么大数据有什么典型特征呢?即数据类型繁多、数据体量巨大、价值密度低即处理速度快。本书也正是将注意力集中在了极大规模数据上的挖掘,而且...
評分当今时代大规模数据爆炸的速度是惊人的,当然,其应用也是越来越广泛的,从传统的零售业到复杂的商业世界,到处都能见到它的身影。那么大数据有什么典型特征呢?即数据类型繁多、数据体量巨大、价值密度低即处理速度快。本书也正是将注意力集中在了极大规模数据上的挖掘,而且...
評分读技术书于我而言就像高中物理老师说的那样:一看就懂、一说就糊、一写就错。为了不马上遗忘昨天刚刚看完的这本书,决定写点东西以帮助多少年之后还有那么一点点记忆。好吧,开写。 1. 总体来说,数据挖掘时数据模型的发现过程。而数据建模的方法可以归纳为两种:数...
評分麻烦支那猪以后翻译外文书籍,先找个稍微懂行的把书看一遍行吗! 鉴于中文翻译缩水不准的情况,本掉千辛万苦找来英文原版,一看到目录,本屌就硬了,尼玛作者太牛逼了! 最新补充一句,话说如果这本书的名字叫做类似《数据挖掘基础》的话,本屌绝壁不喷它。本来就是基础的基...
評分本来是计划读英文版《Mining of Massive Datasets》的,但看到打折,而且译者在序言中信誓旦旦地说翻译的很用心,就买了中文的。结果读了第一章就读不下去了,中文表述太烂了,很多句子让人产生无限歧义,磕磕绊绊,叫人生厌。因此决定再次放弃这样的中文翻译书。
Mining of Massive Datasets pdf epub mobi txt 電子書 下載 2024