Udvidet returret til d. 31. januar 2025

Machine Learning: Theoretical Foundations and Practical Applications

Bag om Machine Learning: Theoretical Foundations and Practical Applications

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9¿12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789813365179
  • Indbinding:
  • Hardback
  • Sideantal:
  • 172
  • Udgivet:
  • 20. april 2021
  • Udgave:
  • 12021
  • Størrelse:
  • 155x235x0 mm.
  • Vægt:
  • 454 g.
  • BLACK WEEK
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 13. december 2024
Forlænget returret til d. 31. januar 2025

Beskrivelse af Machine Learning: Theoretical Foundations and Practical Applications

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9¿12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

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