Machine Learning in Cognitive Iot

Kumar, Neeraj, Makkar, Aaisha

  • 出版商: CRC
  • 出版日期: 2020-05-28
  • 售價: $3,465
  • 貴賓價: 9.5$3,292
  • 語言: 英文
  • 頁數: 256
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 0367359162
  • ISBN-13: 9780367359164
  • 相關分類: Machine Learning物聯網 IoT
  • 立即出貨 (庫存=1)

商品描述

This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIoT). Machine learning is explored by covering all the technical issues and various models used for data analytics during decision making at different steps. It initiates with IoT basics, its history, architecture and applications followed by capabilities of CIoT in real world and description of machine learning (ML) in data mining. Further, it explains various ML techniques and paradigms with different phases of data pre-processing and feature engineering. Each chapter includes sample questions to help understand concepts of ML used in different applications.

  • Explains integration of Machine Learning in IoT for building an efficient decision support system
  • Covers IoT, CIoT, machine learning paradigms and models
  • Includes implementation of machine learning models in R
  • Help the analysts and developers to work efficiently with emerging technologies such as data analytics, data processing, Big Data, Robotics
  • Includes programming codes in Python/Matlab/R alongwith practical examples, questions and multiple choice questions

商品描述(中文翻譯)

本書涵蓋了互聯網的不同技術以及認知物聯網(CIoT)中涉及的機器學習能力。通過涵蓋在不同步驟的決策過程中用於數據分析的所有技術問題和各種模型,探索了機器學習。它從物聯網的基礎知識、歷史、架構和應用開始,然後介紹了現實世界中CIoT的能力以及數據挖掘中的機器學習(ML)的描述。此外,它還解釋了各種ML技術和範例,以及數據預處理和特徵工程的不同階段。每章包括樣本問題,以幫助理解在不同應用中使用的ML概念。


  • 解釋了將機器學習集成到物聯網中以構建高效的決策支持系統

  • 涵蓋了物聯網、CIoT、機器學習範例和模型

  • 包括在R中實現機器學習模型

  • 幫助分析師和開發人員高效地使用新興技術,如數據分析、數據處理、大數據、機器人技術

  • 包括Python/Matlab/R的編程代碼,以及實際範例、問題和多選題

作者簡介

Dr. Neeraj Kumar is working as Full Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala (Pb.), India. Prof. Neeraj is an internationally renowned researcher in the areas of VANET & CPS Smart Grid & IoT Mobile Cloud computing & Big Data and Cryptography. He has published more than 300 technical research papers in leading journals and conferences from IEEE, Elsevier, Springer, John Wiley, and Taylor and Francis. He has guided many research scholars leading to Ph.D. and M.E./M.Tech. He is member of the Cyber-Physical Systems and Security (CPSS) research group. He has research funding from DST, CSIR, UGC, and TCS. He has won best papers awards from IEEE ICC and IEEE Systems Journals 2018. He is a senior member of IEEE and is in the editorial board of various journals of repute.

 

Dr. Aaisha Makkar received her Bachelor of Computer Applications degree from Panjab University, Chandigarh, India in 2010 and Master of Computer Applications from National Institute of Technology (NIT), Kurukshetra, India in 2013. She had worked as an Assistant Professor in Computer Application Department of NIT, Kurukshetra. She obtained her Ph.D. degree from Computer Science and Engineering Department in Thapar Institute of Engineering &Technology, Patiala (Punjab), India. Her research interests in data mining, web mining, algorithms, machine learning and Internet of thing. She has experience of more than 10 years in teaching and research. He has more than 10 research publications in good journals of repute.

作者簡介(中文翻譯)

Dr. Neeraj Kumar是印度帕蒂亞拉(旁遮普邦)塔帕爾工程技術學院計算機科學與工程系的全職教授。Neeraj教授在VANET和CPS智能電網和物聯網移動雲計算和大數據以及密碼學等領域是國際知名的研究者。他在IEEE、Elsevier、Springer、John Wiley和Taylor and Francis等領先期刊和會議上發表了300多篇技術研究論文。他指導了許多研究學者完成博士和碩士學位。他是Cyber-Physical Systems and Security (CPSS)研究小組的成員。他獲得了來自DST、CSIR、UGC和TCS的研究資助。他在2018年獲得了IEEE ICC和IEEE Systems Journals的最佳論文獎。他是IEEE的高級會員,並擔任多個知名期刊的編輯委員會成員。

Dr. Aaisha Makkar於2010年在印度昌迪加爾的旁遮普大學獲得計算機應用學士學位,並於2013年在印度國家技術學院(NIT)庫魯克薛特拉獲得計算機應用碩士學位。她曾在庫魯克薛特拉的NIT計算機應用系擔任助理教授。她在帕蒂亞拉(旁遮普邦)塔帕爾工程技術學院計算機科學與工程系獲得了博士學位。她的研究興趣包括數據挖掘、網絡挖掘、算法、機器學習和物聯網。她在教學和研究方面擁有超過10年的經驗。她在知名期刊上發表了10多篇研究論文。

目錄大綱

Chapter 1: Internet of Things Chapter 2: Cognitive Internet of Things Chapter 3: Data mining in IoT Chapter 4: Machine Learning Techniques Chapter 5: R Programming Chapter 6: Machine Learning Paradigms Chapter 7: Different Machine Learning Models Chapter 8: Data Processing Chapter 9: Feature Engineering and Optimization Chapter 10: Evaluation and Validation of Results Chapter 11: Solutions Chapter 12: Data Set Bibliography

目錄大綱(中文翻譯)

第一章:物聯網
第二章:認知物聯網
第三章:物聯網中的數據挖掘
第四章:機器學習技術
第五章:R程式設計
第六章:機器學習範式
第七章:不同的機器學習模型
第八章:數據處理
第九章:特徵工程和優化
第十章:結果評估和驗證
第十一章:解決方案
第十二章:數據集參考文獻