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2024-05-20
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.
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。
評分行文很流暢,看到下麵很多人說翻譯的問題,由此推薦原版。配閤網課還是挺淺顯的,例子舉得也挺多,自學也可以。步驟寫的也很細,有條件完全可以照著碼,不晦澀,小白很喜歡。
評分下學期課程參考textbook,聽說professor還不錯,打算好好學一下這門課
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。
評分行文很流暢,看到下麵很多人說翻譯的問題,由此推薦原版。配閤網課還是挺淺顯的,例子舉得也挺多,自學也可以。步驟寫的也很細,有條件完全可以照著碼,不晦澀,小白很喜歡。
我真的不能忍受一帮子没读过此书,没写过代码,没搞过大数据的外行人在这边乱喷这本书。对豆瓣这本书的评价实在是太失望了。 这是我读到的第一本真正讲“大数据”思路的书。 面对海量数据的时候,我们的软件架构也会跟着发生变化。当你的数据量在内存里放不下的时候,你就得考...
評分 評分 評分只看了两章,所有真心不好打分。这其实是本数学书,而且是一本入门书。这本书的目标读者不是工程师,而是读研或者读博的学生。如果你本身就有数据挖掘后者机器学习的背景,或者就是很喜欢数学,我还是很推荐这本书的,学习新东西总是很有趣的。
Mining of Massive Datasets pdf epub mobi txt 電子書 下載 2024