Big Data Analytics: Systems, Algorithms, Applications
暫譯: 大數據分析：系統、演算法、應用

Prabhu, C. S. R., Chivukula, Aneesh Sreevallabh, Mogadala, Aditya

Big Data Analytics: Systems, Algorithms, Applications
  • 出版商: Springer
  • 出版日期: 2019-10-24
  • 售價: $4,100
  • 貴賓價: 9.5 折 $3,895
  • 語言: 英文
  • 頁數: 412
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 9811500932
  • ISBN-13: 9789811500930
  • 相關分類: 大數據 Big-data、Algorithms-data-structures、Data Science

    • 海外代購書籍(需單獨結帳)

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商品描述

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning - including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

商品描述(中文翻譯)

本書提供了對大數據及其分析技術、技術和應用的全面調查。大數據現象正日益影響各行各業，產生一個新興的信息生態系統。在應用方面，本書詳細描述了大數據分析在社會語義網挖掘、銀行和金融服務、資本市場、保險、廣告、推薦系統、生物信息學、物聯網（IoT）和雲端計算等重要領域的各種應用領域，然後深入探討安全和隱私問題。關於機器學習技術，本書介紹了所有標準的學習算法，包括監督式、半監督式和非監督式技術，如聚類和強化學習技術，以執行集體深度學習。多層次和非線性學習的大數據也有涵蓋。接著，本書強調了在大型IT公司（如Google、Facebook、LinkedIn和Microsoft）成功實施大數據分析的實際案例研究。針對德意志銀行、能源供應商Opower、達美航空和中國城市交通應用等領域公司進行的多部門案例研究，則是本書的寶貴補充。鑒於本書對大數據分析的全面涵蓋，它為本科生、研究生、研究人員、教育工作者和IT專業人士提供了一個獨特的資源。

作者簡介

Dr. Chivukula Sree Rama Prabhu has held prestigious positions with Government of India and various institutions. He retired as Director General of the National Informatics Centre (NIC), Ministry of Electronics and Information Technology, Government of India, New Delhi, and has worked with Tata Consultancy Services (TCS), CMC, TES and TELCO (now Tata Motors). He was also faculty for the Programs of the APO (Asian Productivity Organization). He has taught and researched at the University of Central Florida, Orlando, USA, and also had a brief stint as a Consultant to NASA. He was Chairman of the Computer Society of India (CSI), Hyderabad Chapter. He is presently working as an Advisor (Honorary) at KL University, Vijayawada, Andhra Pradesh, and as a Director of Research and Innovation at Keshav Memorial Institute of Technology (KMIT), Hyderabad.He received his Master's degree in Electrical Engineering with specialization in Computer Science from the Indian Institute of Technology, Bombay. He has guided many Master's and doctoral students in research areas such as Big Data.Dr. Aneesh Sreevallabh Chivukula is currently a Research Scholar at the Advanced Analytics Institute, University of Technology Sydney (UTS), Australia. Previously, he chiefly worked in computational data science-driven product development at Indian startup companies and research labs. He received his M.S. degree from the International Institute of Information Technology (IIIT), Hyderabad. His research interests include machine learning, data mining, pattern recognition, big data analytics and cloud computing.Dr. Aditya Mogadala is a postdoc in the Language Science and Technology at Saarland University. His research concentrates on the general area of Deep/Representation learning applied for integration of external real-world/common-sense knowledge (e.g., vision and knowledge graphs) into natural language sequence generation models. Before Postdoc, he was a PhD student and Research Associate at the Karlsruhe Institute of Technology, Germany. He holds B.Tech and M.S. degree from the IIIT, Hyderabad, and has worked as a Software Engineer at IBM India Software Labs.Mr. Rohit Ghosh currently works at Qure, Mumbai. He previously served as a Data Scientist for ListUp, and for Data Science Labs. Holding a B.Tech. from the IIT Mumbai, his work involves R&D areas in computer vision, deep learning, reinforcement learning (mostly related to trading strategies) and cryptocurrencies.Dr. Jenila Livingston is an Associate Professor with the CSE Dept at VIT, Chennai. Her teaching foci and research interests include artificial intelligence, soft computing, and analytics.

作者簡介(中文翻譯)

Dr. Chivukula Sree Rama Prabhu 曾在印度政府及多個機構擔任重要職位。他以印度電子與資訊科技部國家資訊中心（NIC）總幹事的身份退休，並曾在塔塔顧問公司（TCS）、CMC、TES 和 TELCO（現為塔塔汽車）工作。他也曾擔任亞洲生產力組織（APO）計畫的教學工作。他曾在美國佛羅里達州奧蘭多的中央佛羅里達大學教授及研究，並短暫擔任 NASA 的顧問。他是印度計算機學會（CSI）海得拉巴分會的主席。目前，他在安得拉邦維傑亞瓦達的 KL 大學擔任榮譽顧問，並在海得拉巴的 Keshav Memorial Institute of Technology（KMIT）擔任研究與創新主任。他在印度孟買的印度理工學院獲得電機工程碩士學位，專攻計算機科學，並指導過許多碩士及博士生，研究領域包括大數據。

Dr. Aneesh Sreevallabh Chivukula 目前是澳大利亞悉尼科技大學（UTS）高級分析研究所的研究學者。他之前主要在印度的初創公司和研究實驗室從事計算數據科學驅動的產品開發。他在海得拉巴的國際資訊技術學院（IIIT）獲得碩士學位。他的研究興趣包括機器學習、數據挖掘、模式識別、大數據分析和雲計算。

Dr. Aditya Mogadala 是薩爾蘭大學語言科學與技術的博士後研究員。他的研究集中在深度/表示學習的一般領域，應用於將外部現實世界/常識知識（例如，視覺和知識圖譜）整合到自然語言序列生成模型中。在博士後之前，他是德國卡爾斯魯厄理工學院的博士生和研究助理。他擁有來自 IIIT 海得拉巴的 B.Tech 和 M.S. 學位，並曾在 IBM 印度軟體實驗室擔任軟體工程師。

Mr. Rohit Ghosh 目前在印度孟買的 Qure 工作。他之前擔任 ListUp 的數據科學家，以及數據科學實驗室的數據科學家。他擁有來自 IIT 孟買的 B.Tech 學位，工作涉及計算機視覺、深度學習、強化學習（主要與交易策略相關）和加密貨幣的研發領域。

Dr. Jenila Livingston 是印度金奈 VIT 大學計算機科學與工程系的副教授。她的教學重點和研究興趣包括人工智慧、軟計算和分析。

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