Deploying AI Models: From Research to Real-World Applications: 13 (AI from Scratch : Step-by-Step Guide to Mastering Artificial Intelligence) - Softcover
Book 13 of 16: AI from Scratch : Step-by-Step Guide to Mastering Artificial Intelligence
Synopsis
Artificial intelligence is transforming industries, but building an AI model is only half the battle. The real challenge lies in deploying, scaling, and maintaining AI models in real-world applications. Deploying AI Models: From Research to Real-World Applications is a step-by-step guide that helps you transition AI models from the research phase to production-ready systems.
This book, the 13th installment in the AI from Scratch series, focuses on practical AI deployment strategies—from cloud and edge deployment to on-premises solutions, API integration, and MLOps automation. You’ll explore how to optimize model performance, manage data pipelines, monitor AI systems, and ensure security and compliance.
Whether you are a machine learning engineer, data scientist, software developer, or AI enthusiast, this book provides the technical insights and real-world case studies needed to successfully deploy AI models at scale.
What You’ll Learn
- AI Model Lifecycle – Understand the transition from research to production
- Cloud Deployment – Deploy AI models on AWS SageMaker, Google Vertex AI, and Azure ML
- Edge AI Deployment – Optimize and run AI models on mobile and IoT devices
- On-Premises AI Deployment – Deploy AI using Kubernetes, Docker, and private servers
- MLOps & Automation – Implement CI/CD pipelines for continuous model updates
- Monitoring & Maintenance – Detect model drift, optimize performance, and retrain models
- Security & Ethics – Address privacy concerns, AI bias, and compliance regulations
- Industry Case Studies – Learn from AI deployment in healthcare, finance, e-commerce, and more
Who Should Read This Book?
- AI Practitioners & Researchers – Learn how to take AI models beyond research
- Machine Learning Engineers & Data Scientists – Master AI deployment best practices
- Software Developers – Integrate AI models into applications via APIs and microservices
- Business Leaders & AI Strategists – Understand how to implement scalable AI solutions
Why This Book?
- Hands-On Approach – Practical examples and deployment scripts
- Comprehensive Coverage – Cloud, edge, on-premises, APIs, and MLOps in one book
- Real-World Case Studies – Learn from successful AI deployments across industries
- Future-Proof Your Skills – Stay ahead with the latest AI deployment trends
By the end of this book, you will be fully equipped to deploy AI models efficiently and at scale—ensuring that your AI solutions deliver real-world impact.
Turn your AI models into powerful, production-ready applications today!
"synopsis" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. Artificial intelligence is transforming industries, but building an AI model is only half the battle. The real challenge lies in deploying, scaling, and maintaining AI models in real-world applications. Deploying AI Models: From Research to Real-World Applications is a step-by-step guide that helps you transition AI models from the research phase to production-ready systems. This book, the 13th installment in the AI from Scratch series, focuses on practical AI deployment strategies-from cloud and edge deployment to on-premises solutions, API integration, and MLOps automation. You'll explore how to optimize model performance, manage data pipelines, monitor AI systems, and ensure security and compliance. Whether you are a machine learning engineer, data scientist, software developer, or AI enthusiast, this book provides the technical insights and real-world case studies needed to successfully deploy AI models at scale. What You'll LearnAI Model Lifecycle - Understand the transition from research to productionCloud Deployment - Deploy AI models on AWS SageMaker, Google Vertex AI, and Azure MLEdge AI Deployment - Optimize and run AI models on mobile and IoT devicesOn-Premises AI Deployment - Deploy AI using Kubernetes, Docker, and private serversMLOps & Automation - Implement CI/CD pipelines for continuous model updatesMonitoring & Maintenance - Detect model drift, optimize performance, and retrain modelsSecurity & Ethics - Address privacy concerns, AI bias, and compliance regulationsIndustry Case Studies - Learn from AI deployment in healthcare, finance, e-commerce, and moreWho Should Read This Book?AI Practitioners & Researchers - Learn how to take AI models beyond researchMachine Learning Engineers & Data Scientists - Master AI deployment best practicesSoftware Developers - Integrate AI models into applications via APIs and microservicesBusiness Leaders & AI Strategists - Understand how to implement scalable AI solutionsWhy This Book?Hands-On Approach - Practical examples and deployment scriptsComprehensive Coverage - Cloud, edge, on-premises, APIs, and MLOps in one bookReal-World Case Studies - Learn from successful AI deployments across industriesFuture-Proof Your Skills - Stay ahead with the latest AI deployment trendsBy the end of this book, you will be fully equipped to deploy AI models efficiently and at scale-ensuring that your AI solutions deliver real-world impact. Turn your AI models into powerful, production-ready applications today! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798310661011
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Paperback. Condition: new. Paperback. Artificial intelligence is transforming industries, but building an AI model is only half the battle. The real challenge lies in deploying, scaling, and maintaining AI models in real-world applications. Deploying AI Models: From Research to Real-World Applications is a step-by-step guide that helps you transition AI models from the research phase to production-ready systems. This book, the 13th installment in the AI from Scratch series, focuses on practical AI deployment strategies-from cloud and edge deployment to on-premises solutions, API integration, and MLOps automation. You'll explore how to optimize model performance, manage data pipelines, monitor AI systems, and ensure security and compliance. Whether you are a machine learning engineer, data scientist, software developer, or AI enthusiast, this book provides the technical insights and real-world case studies needed to successfully deploy AI models at scale. What You'll LearnAI Model Lifecycle - Understand the transition from research to productionCloud Deployment - Deploy AI models on AWS SageMaker, Google Vertex AI, and Azure MLEdge AI Deployment - Optimize and run AI models on mobile and IoT devicesOn-Premises AI Deployment - Deploy AI using Kubernetes, Docker, and private serversMLOps & Automation - Implement CI/CD pipelines for continuous model updatesMonitoring & Maintenance - Detect model drift, optimize performance, and retrain modelsSecurity & Ethics - Address privacy concerns, AI bias, and compliance regulationsIndustry Case Studies - Learn from AI deployment in healthcare, finance, e-commerce, and moreWho Should Read This Book?AI Practitioners & Researchers - Learn how to take AI models beyond researchMachine Learning Engineers & Data Scientists - Master AI deployment best practicesSoftware Developers - Integrate AI models into applications via APIs and microservicesBusiness Leaders & AI Strategists - Understand how to implement scalable AI solutionsWhy This Book?Hands-On Approach - Practical examples and deployment scriptsComprehensive Coverage - Cloud, edge, on-premises, APIs, and MLOps in one bookReal-World Case Studies - Learn from successful AI deployments across industriesFuture-Proof Your Skills - Stay ahead with the latest AI deployment trendsBy the end of this book, you will be fully equipped to deploy AI models efficiently and at scale-ensuring that your AI solutions deliver real-world impact. Turn your AI models into powerful, production-ready applications today! 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 # 9798310661011
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