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Autor(en): 
  • Abhishek Nandy
  • Manisha Biswas
  • Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2017  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / B / Professional and Applied Computing / Programming & scripting languages# general / Programming Language / python / Python (Computer program language)
    ISBN:  9781484232842 
    EAN-Code: 
    9781484232842 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 12 mm 
    Gewicht:  292 gr 
    Seiten:  167 
    Illustration:  XIII, 167 p. 173 illus., 157 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. 

    Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI  before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning.
     
    The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where reinforcement learning can be used. 

    You will:
    • Absorb the core concepts of the reinforcement learning process
    • Use advanced topics of deep learning and AI
    • Work with Open AI Gym, Open AI, and Python 
    • Harness reinforcement learning with TensorFlow and Keras using Python
      
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