Applied Learning Algorithms for Intelligent IoT (Record no. 4810)
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000 -LEADER | |
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fixed length control field | 03386cam a2200493Mu 4500 |
001 - CONTROL NUMBER | |
control field | 9781003119838 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | FlBoTFG |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240213122824.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
fixed length control field | m o d |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr cnu---unuuu |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 210911s2021 xx o ||| 0 eng d |
040 ## - CATALOGING SOURCE | |
Original cataloging agency | OCoLC-P |
Language of cataloging | eng |
Transcribing agency | OCoLC-P |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781000461367 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 100046136X |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781003119838 |
Qualifying information | (electronic bk.) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 1003119832 |
Qualifying information | (electronic bk.) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781000461350 |
Qualifying information | (electronic bk. : PDF) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 1000461351 |
Qualifying information | (electronic bk. : PDF) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
Canceled/invalid ISBN | 0367635941 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
Canceled/invalid ISBN | 9780367635947 |
035 ## - SYSTEM CONTROL NUMBER | |
System control number | (OCoLC)1267762820 |
035 ## - SYSTEM CONTROL NUMBER | |
System control number | (OCoLC-P)1267762820 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q325.5 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM |
Subject category code subdivision | 004000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM |
Subject category code subdivision | 044000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UT |
Source | bicssc |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 |
Edition number | 23 |
245 00 - TITLE STATEMENT | |
Title | Applied Learning Algorithms for Intelligent IoT |
Medium | [electronic resource]. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
Place of publication, distribution, etc. | Milton : |
Name of publisher, distributor, etc. | Auerbach Publishers, Incorporated, |
Date of publication, distribution, etc. | 2021. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 1 online resource (369 p.) |
500 ## - GENERAL NOTE | |
General note | Description based upon print version of record. |
520 ## - SUMMARY, ETC. | |
Summary, etc. | This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics: Cognitive machines and devices Cyber physical systems (CPS) The Internet of Things (IoT) and industrial use cases Industry4.0 for smarter manufacturing Predictive and prescriptive insights for smarter systems Machine vision and intelligence Natural interfaces K-means clustering algorithm Support vector machine (SVM) algorithm A priori algorithms Linear and logistic regression Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights. This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book's detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research. |
588 ## - SOURCE OF DESCRIPTION NOTE | |
Source of description note | OCLC-licensed vendor bibliographic record. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | Machine learning. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | Algorithms. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | Internet of things. |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | COMPUTERS / Artificial Intelligence |
Source of heading or term | bisacsh |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | COMPUTERS / Neural Networks |
Source of heading or term | bisacsh |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Chelliah, Pethuru Raj. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Sakthivel, Usha. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Nagarajan, Susila. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Materials specified | Taylor & Francis |
Uniform Resource Identifier | <a href="https://www.taylorfrancis.com/books/9781003119838">https://www.taylorfrancis.com/books/9781003119838</a> |
856 42 - ELECTRONIC LOCATION AND ACCESS | |
Materials specified | OCLC metadata license agreement |
Uniform Resource Identifier | <a href="http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf">http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf</a> |
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