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Deep Reinforcement Learning and Its Industrial Use Cases - Shubham Mahajan - Bog

Deep Reinforcement Learning and Its Industrial Use Casesaf Shubham Mahajan
Bag om Deep Reinforcement Learning and Its Industrial Use Cases

"Deep Reinforcement Learning and its Industrial Use Cases: Harnessing AI for Real-World Applications" is an essential guide that supplies complex theories, practical insights, and diverse case studies behind deep reinforcement learning. This book offers a comprehensive look into how DLR is revolutionizing fields by implementing advanced algorithms in a variety of industries to solve real-world problems. Beyond the realm of successes of DLR, it critically examines challenges, pitfalls, and ethical considerations. This research and knowledge explore insights to meet the needs of curious enthusiasts eager to understand the cutting-edge technology shaping our future. Throughout the pages of this book, we seek to discover the inner workings of DLR and its real-world applications. We start by laying down the foundational principles of reinforcement learning and building up to advanced DLR algorithms and techniques. Along the way, we delve into diverse case studies, examining how leading organizations harness the power of DLR to drive innovation and gain a competitive edge. From financial trading to autonomous manufacturing systems, each case study offers valuable insights into the practical considerations and challenges involved in deploying DLR solutions.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781394272556
  • Indbinding:
  • Hardback
  • Udgivet:
  • 18. September 2024
  • Kan forudbestilles.
  • 18. September 2024

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Beskrivelse af Deep Reinforcement Learning and Its Industrial Use Cases

"Deep Reinforcement Learning and its Industrial Use Cases: Harnessing AI for Real-World Applications" is an essential guide that supplies complex theories, practical insights, and diverse case studies behind deep reinforcement learning. This book offers a comprehensive look into how DLR is revolutionizing fields by implementing advanced algorithms in a variety of industries to solve real-world problems. Beyond the realm of successes of DLR, it critically examines challenges, pitfalls, and ethical considerations. This research and knowledge explore insights to meet the needs of curious enthusiasts eager to understand the cutting-edge technology shaping our future. Throughout the pages of this book, we seek to discover the inner workings of DLR and its real-world applications. We start by laying down the foundational principles of reinforcement learning and building up to advanced DLR algorithms and techniques. Along the way, we delve into diverse case studies, examining how leading organizations harness the power of DLR to drive innovation and gain a competitive edge. From financial trading to autonomous manufacturing systems, each case study offers valuable insights into the practical considerations and challenges involved in deploying DLR solutions.

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