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Autor(en): 
  • Tony Jebara
  • Machine Learning: Discriminative and Generative 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 4 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2003  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / B / Computer Imaging, Vision, Pattern Recognition and Graphics / Computer Vision / Data Warehousing / engineering / Extension;computer science;learning;machine learning / Image processing / Information Retrieval / Information Storage and Retrieval / Optical data processing / Probability & statistics / Statistics / Statistics, general
    ISBN:  9781402076473 
    EAN-Code: 
    9781402076473 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 18 mm 
    Gewicht:  4616 gr 
    Seiten:  200 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it bridges the two schools of thought together within a common framework, elegantly connecting their various theories and making one common big-picture. Also, this bridge brings forth new hybrid discriminative-generative tools that combine the strengths of both camps. This book serves multiple purposes as well. The framework acts as a scientific breakthrough, fusing the areas of generative and discriminative learning and will be of interest to many researchers. However, as a conceptual breakthrough, this common framework unifies many previously unrelated tools and techniques and makes them understandable to a larger portion of the public. This gives the more practical-minded engineer, student and the industrial public an easy-access and more sensible road map into the world of machine learning. Machine Learning: Discriminative and Generative is designed for an audience composed of researchers & practitioners in industry and academia. The book is also suitable as a secondary text for graduate-level students in computer science and engineering.

      
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