A Practitioner's Guide to Building Production Systems
Buch, Englisch, Format (B × H): 178 mm x 254 mm
ISBN: 979-8-8688-3200-0
Verlag: APRESS L.P.
Most enterprise AI projects succeed as pilots and fail at scale. The difference is almost always the system, not the model.
Embark on a journey through the full Azure AI ecosystem, from the early days of Azure Machine Learning to the intelligence of Microsoft Foundry, bridging classical ML, multi-modal AI services, and next-generation generative and agentic systems. Design data foundations, choose and deploy models, orchestrate RAG and multi-agent workflows over MCP, operationalize and govern the whole stack with Responsible AI for real-world systems. Explore the seven-layer architecture that underpins production AI systems: Foundation, Knowledge, Intelligence, Orchestration, Experience, Observability, and Trust, and use it to build hybrid ML-GenAI applications, enterprise agents, and Autopilots. By the end of the book, readers will not only understand the mechanics of Azure’s AI ecosystem, but also the philosophy behind building intelligent, explainable, secure, and sustainable AI for the Agentic Era.
In today’s rapidly evolving AI landscape, organizations face the critical challenge of implementing AI solutions that are both powerful and practical. This book bridges the gap between Azure’s vast AI capabilities and real-world business needs, making it essential for professionals who need to deliver results — not just understand concepts. The combination of comprehensive coverage, hands-on implementation guidance, and strategic architectural frameworks makes it indispensable for anyone responsible for Azure AI initiatives.
This is not a survey of Azure services. It is a guide to building systems that work.
What You Will Learn:
- Master Azure’s complete AI ecosystem, from machine learning and pre-built AI services to Azure OpenAI, MAI models, and Microsoft Foundry
- Go beyond theory with hands-on Azure exercises, production deployment strategies, reference architectures, and real case studies
- Build, deploy, and operate AI solutions that span predictive models, generative applications, RAG systems, and enterprise agents
- Peek into the world of Agents, multi-agent frameworks, MCP, and quantum ML
Who This Book is For:
This book is designed for data scientists, AI/ML engineers, solution architects, and platform engineers who want to build end-to-end AI and Machine Learning systems on Azure. It is equally useful for tech leads and engineering managers shaping enterprise AI strategy in the Agentic Era.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Chapter 1: The Evolution of Azure AI and ML: From Models to Systems.- Chapter 2: Designing Enterprise AI Systems: Intent and Architecture.- Chapter 3: The Foundation Layer: Building the Azure AI Platform.- Chapter 4: The Knowledge Layer: Data, Retrieval and Grounding.- Chapter 5: The Intelligence Layer: From Prebuilt AI to Custom Models.- Chapter 6: Deploying and Serving Intelligence.- Chapter 7: The Orchestration Layer: Workflows, RAG, and Generative AI.- Chapter 8: Microsoft Foundry: The Unified AI and Agent Platform.- Chapter 9: Agentic AI Systems: Tools, MCP, and Multi-Agent Patterns.- Chapter 10: The Experience Layer: Integration and Human-AI Interaction.- Chapter 11: The Observability Layer: MLOps, GenAIOps, and Production Operations.- Chapter 12: The Trust Layer: Responsible AI, Governance, and Security.- Chapter 13: Enterprise AI in Action: Patterns and Lessons.- Chapter 14: Building for Change: The AI Horizon.
