Algorithms and Data Structures for Massive Datasets
Medjedovic, Dzejla, Tahirovic, Emin, Dedovic, Ines
- 出版商: Manning
- 出版日期: 2022-07-05
- 售價: $2,150
- 貴賓價: 9.5 折 $2,043
- 語言: 英文
- 頁數: 304
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617298034
- ISBN-13: 9781617298035
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相關分類:
Algorithms-data-structures
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相關翻譯:
漫畫算法與數據結構(大規模數據集) (簡中版)
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商品描述
In Algorithms and Data Structures for Massive Datasets, you'll discover methods for reducing and sketching data so it fits in small memory without losing accuracy, and unlock the algorithms and data structures that form the backbone of a big data system.
Data structures and algorithms that are great for traditional software may quickly slow or fail altogether when applied to huge datasets. Algorithms and Data Structures for Massive Datasets introduces a toolbox of new techniques that are perfect for handling modern big data applications.
In Algorithms and Data Structures for Massive Datasets, you'll discover methods for reducing and sketching data so it fits in small memory without losing accuracy, and unlock the algorithms and data structures that form the backbone of a big data system. Filled with fun illustrations and examples from real-world businesses, you'll learn how each of these complex techniques can be practically applied to maximize the accuracy and throughput of big data processing and analytics.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
商品描述(中文翻譯)
在《大數據的演算法與資料結構》一書中,您將會發現一些方法,可以將資料進行壓縮和簡化,使其在記憶體有限的情況下仍能保持準確性,同時也會揭示構成大數據系統核心的演算法和資料結構。傳統軟體中適用的資料結構和演算法在處理大型資料集時可能會變得緩慢或完全失效。《大數據的演算法與資料結構》介紹了一系列適用於處理現代大數據應用的新技術。在這本書中,您將會發現一些方法,可以將資料進行壓縮和簡化,使其在記憶體有限的情況下仍能保持準確性,同時也會揭示構成大數據系統核心的演算法和資料結構。書中還包含了來自真實企業的有趣插圖和實例,讓您了解這些複雜技術如何實際應用於大數據處理和分析,以最大程度地提高準確性和處理效能。購買印刷版書籍還包括一本免費的電子書(PDF、Kindle和ePub格式),由Manning Publications提供。
作者簡介
Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab of the computer science department at Stony Brook University, NY in 2014. She has worked on a number of projects in algorithms for massive data, taught algorithms at various levels and also spent some time at Microsoft.
Emin Tahirovic earned his doctorate in biostatistics from UPenn in 2016, and his master's degree in theoretical computer science from Goethe University in Frankfurt in 2008. He has worked for DBahn AG as an IT consultant and he regularly consults on projects for pharma and tech companies.
Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision of the Department of Electrical Engineering at RWTH Aachen University, Germany. She has worked as a researcher at the Research Center Jülich and is currently employed as a software developer for camera systems at Jonas & Redmann, an automation company.
作者簡介(中文翻譯)
Dzejla Medjedovic於2014年在紐約州立大學石溪分校的計算機科學系應用算法實驗室獲得博士學位。她在大數據算法領域參與了多個項目的工作,並在不同層次上教授算法課程,同時也在微軟公司工作過一段時間。
Emin Tahirovic於2016年從賓夕法尼亞大學獲得生物統計學博士學位,並於2008年從法蘭克福歌德大學獲得理論計算機科學碩士學位。他曾在DBahn AG擔任IT顧問,並經常為製藥和科技公司的項目提供諮詢服務。
Ines Dedovic於德國亞琛工業大學電機工程系影像與計算機視覺研究所獲得博士學位。她曾在朱利希研究中心擔任研究員,目前在自動化公司Jonas & Redmann擔任相機系統軟體開發人員的職位。