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Autor(en): 
  • Sara Silva
  • Leonardo Vanneschi
  • Lectures on Intelligent Systems 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Januar 2023  
    Genre:  EDV / Informatik 
     
    ArtificialIntelligence / ArtificialNeuralNetworks / ComputationalIntelligence / Evolutionarycomputing / machinelearning / Optimization
    ISBN:  9783031179211 
    EAN-Code: 
    9783031179211 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 26 mm 
    Gewicht:  711 gr 
    Seiten:  364 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This textbook provides the reader with an essential understanding of computational methods for intelligent systems. These are defined as systems that can solve problems autonomously, in particular problems where algorithmic solutions are inconceivable for humans or not practically executable by computers. Despite the rapidly growing applications in this field, the book avoids application details, instead focusing on computational methods that equip the reader with the methodological tools and competencies necessary to tackle current and future complex applications. The book consists of two parts: computational intelligence methods for optimization, and machine learning. Part I begins with the concept of optimization, and introduces local search algorithms, genetic algorithms, and particle swarm optimization. Part II begins with an introduction to machine learning and covers several methods, many of which can be used as supervised learning algorithms, such as decision treelearning, artificial neural networks, genetic programming, Bayesian learning, support vector machines, and ensemble methods, plus a discussion of unsupervised learning. This textbook is written in a self-contained style, suitable for undergraduate or graduate students in computer science and engineering, and for self-study by researchers and practitioners.

      



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