Machine Learning Approach for Cloud Data Analytics in Iot
暫譯: 雲端數據分析中的機器學習方法與物聯網應用

Mohanty, Sachi Nandan, Chatterjee, Jyotir Moy, Mangla, Monika

Machine Learning Approach for Cloud Data Analytics in Iot
  • 出版商: Wiley
  • 出版日期: 2021-07-27
  • 售價: $8,020
  • 貴賓價: 9.5 折 $7,619
  • 語言: 英文
  • 頁數: 528
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1119785804
  • ISBN-13: 9781119785804
  • 相關分類: Machine Learning、物聯網 IoT、Data Science

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage.

Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media.

Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics.

商品描述(中文翻譯)

在物聯網（IoT）時代，邊緣設備在每一瞬間都會產生巨量數據。這些網絡的主要目的是從收集到的數據中推斷出有意義的信息。為此，這些龐大的數據會被傳輸到雲端，這樣的過程既昂貴又耗時。因此，需要設計一些高效的機制來處理這些龐大的數據，從而迫切需要有效的數據處理技術。可持續計算範式，如雲計算和霧計算，能夠有效地處理性能、存儲和處理能力、維護、安全性、效率、整合、成本、能源和延遲等問題。然而，這需要複雜的分析工具來在優化的時間內解決查詢。因此，針對設計有效且高效的框架以獲取最大優勢的研究正在進行中。

機器學習因其處理大量數據的能力而獲得了無與倫比的普及，並在社交媒體等多個領域中有著廣泛的應用。

《物聯網雲數據分析的機器學習方法》詳細整合了物聯網、雲計算和數據分析的各個方面，從多元的視角進行探討。該書報告了最先進的研究和高級主題，讓讀者了解最新動態，並提供了一種理解和探索物聯網、雲計算和數據分析應用範疇的方法。

作者簡介

Sachi Nandan Mohanty received his PhD from IIT Kharagpur 2015 and he is now an associate professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education, Hyderabad, India.

Jyotir Moy Chatterjee is currently working as an assistant professor in the IT Department at Lord Buddha Education Foundation (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal.

Monika Mangla received her PhD from Thapar Institute of Engineering & Technology, Patiala, Punjab in 2019, and is now an assistant professor in the Department of Computer Engineering at Lokmanya Tilak College of Engineering (LTCoE), Navi Mumbai, India.

Suneeta Satpathy received her PhD from Utkal University, Bhubaneswar, Odisha in 2015, and is now an associate professor in the Department of Computer Science & Engineering at College of Engineering Bhubaneswar (CoEB), Bhubaneswar, India.

Ms. Sirisha Potluri working as assistant professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education, Hyderabad, India.

作者簡介(中文翻譯)

Sachi Nandan Mohanty 於2015年獲得印度卡哈爾古爾印度科技學院（IIT Kharagpur）博士學位，目前是印度海得拉巴ICFAI高等教育基金會計算機科學與工程系的副教授。

Jyotir Moy Chatterjee 目前在尼泊爾加德滿都的佛陀教育基金會（亞洲太平洋科技與創新大學）IT系擔任助理教授。

Monika Mangla 於2019年獲得印度旁遮普省塔帕爾工程與技術學院（Thapar Institute of Engineering & Technology）博士學位，目前是印度新孟買Lokmanya Tilak工程學院（LTCoE）計算機工程系的助理教授。

Suneeta Satpathy 於2015年獲得印度奧里薩邦布巴內斯瓦爾烏特卡爾大學（Utkal University）博士學位，目前是印度布巴內斯瓦爾工程學院（College of Engineering Bhubaneswar, CoEB）計算機科學與工程系的副教授。

Ms. Sirisha Potluri 在印度海得拉巴ICFAI高等教育基金會計算機科學與工程系擔任助理教授。

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