AI Engineering : Building Applications with Foundation Models. - Huyen, Chip.; ProQuest (firma) (Sebastopol : O'Reilly Media, Incorporated, 2025)
Chapter 8. Dataset Engineering -- Data Curation -- Data Quality -- Data Coverage -- Data Quantity -- Data Acquisition and Annotation -- Data Augmentation and Synthesis -- Why Data Synthesis -- Traditional Data Synthesis Techniques -- AI-Powered Data Synthesis -- Model Distillation -- Data Processing -- Inspect Data -- Deduplicate Data -- Clean and Filter Data -- Format Data -- Summary -- Chapter 9. Inference Optimization -- Understanding Inference Optimization -- Inference Overview -- Inference Performance Metrics -- AI Accelerators -- Inference Optimization -- Model Optimization -- Inference Service Optimization -- Summary -- Chapter 10. AI Engineering Architecture and User Feedback -- AI Engineering Architecture -- Step 1. Enhance Context -- Step 2. Put in Guardrails -- Step 3. Add Model Router and Gateway -- Step 4. Reduce Latency with Caches -- Step 5. Add Agent Patterns -- Monitoring and Observability -- AI Pipeline Orchestration -- User Feedback -- Extracting Conversational Feedback -- Feedback Design -- Feedback Limitations -- Summary -- Epilogue -- Index -- About the Author -- Colophon.
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2025. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Keywords: elektronické knihy; electronic books