View in EDS PDF Full Text ePub Full Text

Machine Learning Methods for Engineering Application Development

Saved in:
Bibliographic Details
Title: Machine Learning Methods for Engineering Application Development
Description: This book is a quick review of machine learning methods for engineering applications. It provides an introduction to the principles of machine learning and common algorithms in the first section. Proceeding chapters summarize and analyze the existing scholarly work and discuss some general issues in this field. Next, it offers some guidelines on applying machine learning methods to software engineering tasks. Finally, it gives an outlook into some of the future developments and possibly new research areas of machine learning and artificial intelligence in general.Techniques highlighted in the book include: Bayesian models, support vector machines, decision tree induction, regression analysis, and recurrent and convolutional neural network. Finally, it also intends to be a reference book.Key Features:- Describes real-world problems that can be solved using machine learning- Explains methods for directly applying machine learning techniques to concrete real-world problems- Explains concepts used in Industry 4.0 platforms, including the use and integration of AI, ML, Big Data, NLP, and the Internet of Things (IoT).- It does not require prior knowledge of the machine learning. This book is meant to be an introduction to artificial intelligence (AI), machine earning, and its applications in Industry 4.0. It explains the basic mathematical principles but is intended to be understandable for readers who do not have a background in advanced mathematics.
Authors: Prasad, Lokulwar, Basant, Verma, N, Thillaiarasu, Kailash, Kumar, Mahip, Bartere, Dharam, Singh
Resource Type: eBook.
Subjects: Machine learning
Categories: COMPUTERS / Data Science / Machine Learning, COMPUTERS / Programming / Algorithms, TECHNOLOGY & ENGINEERING / Engineering (General)
Database: eBook Collection (EBSCOhost)
FullText Links:
  – Type: ebook-pdf
  – Type: ebook-epub
Text:
  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 3466668
RelevancyScore: 1110
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1109.74133300781
IllustrationInfo
ImageInfo – Size: thumb
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$3466668$PDF&s=r
– Size: medium
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$3466668$PDF&s=d
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Machine Learning Methods for Engineering Application Development
– Name: Abstract
  Label: Description
  Group: Ab
  Data: This book is a quick review of machine learning methods for engineering applications. It provides an introduction to the principles of machine learning and common algorithms in the first section. Proceeding chapters summarize and analyze the existing scholarly work and discuss some general issues in this field. Next, it offers some guidelines on applying machine learning methods to software engineering tasks. Finally, it gives an outlook into some of the future developments and possibly new research areas of machine learning and artificial intelligence in general.Techniques highlighted in the book include: Bayesian models, support vector machines, decision tree induction, regression analysis, and recurrent and convolutional neural network. Finally, it also intends to be a reference book.Key Features:- Describes real-world problems that can be solved using machine learning- Explains methods for directly applying machine learning techniques to concrete real-world problems- Explains concepts used in Industry 4.0 platforms, including the use and integration of AI, ML, Big Data, NLP, and the Internet of Things (IoT).- It does not require prior knowledge of the machine learning. This book is meant to be an introduction to artificial intelligence (AI), machine earning, and its applications in Industry 4.0. It explains the basic mathematical principles but is intended to be understandable for readers who do not have a background in advanced mathematics.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Prasad%2C+Lokulwar%22">Prasad, Lokulwar</searchLink><br /><searchLink fieldCode="AR" term="%22Basant%2C+Verma%22">Basant, Verma</searchLink><br /><searchLink fieldCode="AR" term="%22N%2C+Thillaiarasu%22">N, Thillaiarasu</searchLink><br /><searchLink fieldCode="AR" term="%22Kailash%2C+Kumar%22">Kailash, Kumar</searchLink><br /><searchLink fieldCode="AR" term="%22Mahip%2C+Bartere%22">Mahip, Bartere</searchLink><br /><searchLink fieldCode="AR" term="%22Dharam%2C+Singh%22">Dharam, Singh</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Machine+Learning%22">COMPUTERS / Data Science / Machine Learning</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Algorithms%22">COMPUTERS / Programming / Algorithms</searchLink><br /><searchLink fieldCode="ZK" term="%22TECHNOLOGY+%26+ENGINEERING+%2F+Engineering+%28General%29%22">TECHNOLOGY & ENGINEERING / Engineering (General)</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=3466668
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 006.31
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Machine learning
        Type: general
    Titles:
      – TitleFull: Machine Learning Methods for Engineering Application Development
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Prasad, Lokulwar
      – PersonEntity:
          Name:
            NameFull: Basant, Verma
      – PersonEntity:
          Name:
            NameFull: N, Thillaiarasu
      – PersonEntity:
          Name:
            NameFull: Kailash, Kumar
      – PersonEntity:
          Name:
            NameFull: Mahip, Bartere
      – PersonEntity:
          Name:
            NameFull: Dharam, Singh
      – PersonEntity:
          Name:
            NameFull: Prasad, Lokulwar
      – PersonEntity:
          Name:
            NameFull: Basant, Verma
      – PersonEntity:
          Name:
            NameFull: N, Thillaiarasu
      – PersonEntity:
          Name:
            NameFull: Kailash, Kumar
      – PersonEntity:
          Name:
            NameFull: Mahip, Bartere
      – PersonEntity:
          Name:
            NameFull: Dharam, Singh
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
            – D: 09
              M: 05
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9789815079197
            – Type: isbn-electronic
              Value: 9789815079180
          Titles:
            – TitleFull: Machine Learning Methods for Engineering Application Development
              Type: main
ResultId 1