Artificial Intelligence in Production: Practical Engineering Beyond Theory
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This monograph addresses the engineering challenges of deploying and operating AI systems in real-world environments. It focuses on data infrastructure for production AI, model deployment constraints, reliability and observability, human-AI interaction, scaling AI in enterprise settings, security and robustness, and economic impact. The book shifts the emphasis from model-centric thinking to system-oriented design, offering actionable frameworks for building resilient, maintainable, and cost-effective industrial AI systems.
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Beschrijving
Bol
This monograph addresses the engineering challenges of deploying and operating AI systems in real-world environments. It focuses on data infrastructure for production AI, model deployment constraints, reliability and observability, human-AI interaction, scaling AI in enterprise settings, security and robustness, and economic impact. The book shifts the emphasis from model-centric thinking to system-oriented design, offering actionable frameworks for building resilient, maintainable, and cost-effective industrial AI systems.
Beschrijving
(2)
Bol
This monograph addresses the engineering challenges of deploying and operating AI systems in real-world environments. It focuses on data infrastructure for production AI, model deployment constraints, reliability and observability, human-AI interaction, scaling AI in enterprise settings, security and robustness, and economic impact. The book shifts the emphasis from model-centric thinking to system-oriented design, offering actionable frameworks for building resilient, maintainable, and cost-effective industrial AI systems.
AmazonPagina's: 72, Paperback, LAP LAMBERT Academic Publishing
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