Grokking Deep Reinforcement Learning - Morales, Miguel
45,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 2-4 Wochen
payback
23 °P sammeln
  • Broschiertes Buch

We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
Miguel Morales is a Senior Software Engineer at Lockheed Martin, Missile and Fire Control-Autonomous Systems. He is also a faculty member at Georgia Institute of Technology where he works as an Instructional Associate for the Reinforcement Learning and Decision Making graduate course. Miguel has worked for numerous other educational and technology companies including Udacity, AT&T, Cisco, and HPE.