Reinforcement Learning is no longer a research topic—it's becoming the engine behind the next generation of enterprise decision-making.
Reinforcement Learning in Production: Use Cases & Safety is a practical, executive-level guide for architects, AI engineers, technology leaders, MLOps professionals, and enterprise decision-makers who want to design, deploy, govern, and scale Reinforcement Learning (RL) systems in real-world production environments.
Rather than focusing on theory alone, this book bridges the gap between research and enterprise implementation, showing how RL can optimize manufacturing, financial services, healthcare, cybersecurity, cloud platforms, supply chains, and intelligent enterprise operations—while maintaining safety, governance, explainability, and human oversight.
Inside you'll learn how to:
Packed with enterprise architectures, implementation strategies, governance frameworks, production best practices, and hands-on architecture challenges, this book delivers the practical knowledge required to build trustworthy, scalable, and business-ready Reinforcement Learning solutions.
Whether you're modernizing enterprise AI platforms, leading digital transformation initiatives, or preparing your organization for the era of autonomous decision intelligence, this book provides the roadmap to move from experimentation to production with confidence.
Build intelligent systems. Deploy them safely. Govern them responsibly. Lead the future of enterprise decision intelligence.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. Print on Demand. N° de réf. du vendeur I-9798184589879
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9798184589879
Quantité disponible : Plus de 20 disponibles