Items related to MLOps LLMOps And Deployment (AI and ML Reference handbooks)
MLOps LLMOps And Deployment (AI and ML Reference handbooks) - Softcover
Book 16 of 22: AI and ML Reference handbooks
Synopsis
Master the complete production lifecycle of Machine Learning and Large Language Models—from experimentation to enterprise deployment.
MLOps, LLMOps and Deployment is a practical, engineer-focused guide that takes you beyond model training and into the real-world challenges of deploying, monitoring, scaling, and maintaining AI systems in production.
Designed for AI Engineers, Machine Learning Engineers, Data Scientists, MLOps Engineers, DevOps Professionals, Cloud Architects, and students preparing for technical interviews, this book explains every major concept using simple language, production examples, architecture diagrams, troubleshooting scenarios, interview questions, and hands-on workflows.
Inside this book, you'll learn:
- Complete end-to-end MLOps lifecycle
- CI, CD, and Continuous Training (CT)
- Model versioning and Model Registry
- Drift detection and production monitoring
- Docker and Kubernetes for ML deployment
- Blue-Green, Canary, Rolling, Shadow, and A/B deployments
- LLMOps fundamentals, prompt versioning, and RAG operations
- Feature Stores and production data pipelines
- Observability, alerting, and incident response
- AI governance, compliance, and model security
- GitOps with ArgoCD, Flux, and Terraform
- AWS SageMaker, Azure ML, and Google Vertex AI implementations
- GPU inference optimization using TensorRT, Triton, CUDA, and vLLM
- Agentic AI workflows, MCP, Guardrails, and Prompt Registries
- Production troubleshooting and enterprise readiness checklists
Every chapter includes:
- Simple explanations
- Real production challenges
- Architecture diagrams
- Practical code examples
- Interview Q&A
- Knowledge checks
- Hands-on exercises
Whether you're deploying your first ML model or building enterprise-scale AI platforms, this book provides the practical knowledge needed to confidently design, deploy, monitor, and operate modern AI systems.
"synopsis" may belong to another edition of this title.
Search results for MLOps LLMOps And Deployment (AI and ML Reference handbooks)
Stock Image
MLOps LLMOps And Deployment (AI and ML Reference handbooks)
Print on DemandSeller: California Books, Miami, FL, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # I-9798190029277
Stock Image
MLOps LLMOps And Deployment
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9798190029277
Buy New
US$ 29.32
US$ 5.56 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
MLOps LLMOps And Deployment (Paperback)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Master the complete production lifecycle of Machine Learning and Large Language Models-from experimentation to enterprise deployment.MLOps, LLMOps and Deployment is a practical, engineer-focused guide that takes you beyond model training and into the real-world challenges of deploying, monitoring, scaling, and maintaining AI systems in production.Designed for AI Engineers, Machine Learning Engineers, Data Scientists, MLOps Engineers, DevOps Professionals, Cloud Architects, and students preparing for technical interviews, this book explains every major concept using simple language, production examples, architecture diagrams, troubleshooting scenarios, interview questions, and hands-on workflows.Inside this book, you'll learn: Complete end-to-end MLOps lifecycleCI, CD, and Continuous Training (CT)Model versioning and Model RegistryDrift detection and production monitoringDocker and Kubernetes for ML deploymentBlue-Green, Canary, Rolling, Shadow, and A/B deploymentsLLMOps fundamentals, prompt versioning, and RAG operationsFeature Stores and production data pipelinesObservability, alerting, and incident responseAI governance, compliance, and model securityGitOps with ArgoCD, Flux, and TerraformAWS SageMaker, Azure ML, and Google Vertex AI implementationsGPU inference optimization using TensorRT, Triton, CUDA, and vLLMAgentic AI workflows, MCP, Guardrails, and Prompt RegistriesProduction troubleshooting and enterprise readiness checklistsEvery chapter includes: Simple explanationsReal production challengesArchitecture diagramsPractical code examplesInterview Q&AKnowledge checksHands-on exercisesWhether you're deploying your first ML model or building enterprise-scale AI platforms, this book provides the practical knowledge needed to confidently design, deploy, monitor, and operate modern AI systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798190029277
Buy New
US$ 33.68
US$ 49.42 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
MLOps LLMOps And Deployment
Published by
Amazon Digital Services LLC - Kdp Aug 2026, 2026
ISBN 13: 9798190029277
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware - Master the complete production lifecycle of Machine Learning and Large Language Models-from experimentation to enterprise deployment.MLOps, LLMOps and Deployment is a practical, engineer-focused guide that takes you beyond model training and into the real-world challenges of deploying, monitoring, scaling, and maintaining AI systems in production.Designed for AI Engineers, Machine Learning Engineers, Data Scientists, MLOps Engineers, DevOps Professionals, Cloud Architects, and students preparing for technical interviews, this book explains every major concept using simple language, production examples, architecture diagrams, troubleshooting scenarios, interview questions, and hands-on workflows.Inside this book, you'll learn: - Complete end-to-end MLOps lifecycle- CI, CD, and Continuous Training (CT)- Model versioning and Model Registry- Drift detection and production monitoring- Docker and Kubernetes for ML deployment- Blue-Green, Canary, Rolling, Shadow, and A/B deployments- LLMOps fundamentals, prompt versioning, and RAG operations- Feature Stores and production data pipelines- Observability, alerting, and incident response- AI governance, compliance, and model security- GitOps with ArgoCD, Flux, and Terraform- AWS SageMaker, Azure ML, and Google Vertex AI implementations- GPU inference optimization using TensorRT, Triton, CUDA, and vLLM- Agentic AI workflows, MCP, Guardrails, and Prompt Registries- Production troubleshooting and enterprise readiness checklistsEvery chapter includes: - Simple explanations- Real production challenges- Architecture diagrams- Practical code examples- Interview Q&A- Knowledge checks- Hands-on exercisesWhether you're deploying your first ML model or building enterprise-scale AI platforms, this book provides the practical knowledge needed to confidently design, deploy, monitor, and operate modern AI systems. Seller Inventory # 9798190029277
Buy New
US$ 58.12
US$ 35.00 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available