Deploying AI Models - Gutiérrez, Gilbert
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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…mehr

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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 >Turn your AI models into powerful, production-ready applications today!
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