Usha Jagannathan (6 results)

Condition: New.

Paperback. Condition: New. Deliver measurable business value by applying strategic, technical, and ethical frameworks to AI initiatives at scaleFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI strategies that align with business goals and maximize ROIImplement enterprise-ready frameworks for MLOps, LLMOps, and Responsible AILearn from real-world case studies spanning industries and AI maturity levelsBook DescriptionAI is only as valuable as the business outcomes it enables, and this hands-on guide shows you how to make that happen. Whether you're a technology leader launching your first AI use case or scaling production systems, you need a clear path from innovation to impact. That means aligning your AI initiatives with enterprise strategy, operational readiness, and responsible practices, and The AI Optimization Playbook gives you the clarity, structure, and insight you need to succeed.Through actionable guidance and real-world examples, you'll learn how to build high-impact AI strategies, evaluate projects based on ROI, secure executive sponsorship, and transition prototypes into production-grade systems. You'll also explore MLOps and LLMOps practices that ensure scalability, reliability, and governance across the AI lifecycle.But deployment is just the beginning. This book goes further to address the crucial need for Responsible AI through frameworks, compliance strategies, and transparency techniques. Written by AI experts and industry leaders, this playbook combines technical fluency with strategic perspective to bridge the business-technology divide so you can confidently lead AI transformation across the enterprise.*Email sign-up and proof of purchase requiredWhat you will learnDesign business-aligned AI strategiesSelect and prioritize AI projects with the highest potential ROIDevelop reliable prototypes and scale them using MLOps pipelinesIntegrate explainability, fairness, and compliance into AI systemsApply LLMOps practices to deploy and maintain generative AI modelsBuild AI agents that support autonomous decision-making at scaleNavigate evolving AI regulations with actionable compliance frameworksBuild a future-ready, ethically grounded AI organizationWho this book is forThis book is for AI/ML leaders and business leaders, CTOs, CIOs, CDAOs, and CAIOs, responsible for driving innovation, operational efficiency, and risk mitigation through artificial intelligence. You should have familiarity with enterprise technology and the fundamentals of AI solution development.

Paperback. Condition: New. Deliver measurable business value by applying strategic, technical, and ethical frameworks to AI initiatives at scaleFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI strategies that align with business goals and maximize ROIImplement enterprise-ready frameworks for MLOps, LLMOps, and Responsible AILearn from real-world case studies spanning industries and AI maturity levelsBook DescriptionAI is only as valuable as the business outcomes it enables, and this hands-on guide shows you how to make that happen. Whether you're a technology leader launching your first AI use case or scaling production systems, you need a clear path from innovation to impact. That means aligning your AI initiatives with enterprise strategy, operational readiness, and responsible practices, and The AI Optimization Playbook gives you the clarity, structure, and insight you need to succeed.Through actionable guidance and real-world examples, you'll learn how to build high-impact AI strategies, evaluate projects based on ROI, secure executive sponsorship, and transition prototypes into production-grade systems. You'll also explore MLOps and LLMOps practices that ensure scalability, reliability, and governance across the AI lifecycle.But deployment is just the beginning. This book goes further to address the crucial need for Responsible AI through frameworks, compliance strategies, and transparency techniques. Written by AI experts and industry leaders, this playbook combines technical fluency with strategic perspective to bridge the business-technology divide so you can confidently lead AI transformation across the enterprise.*Email sign-up and proof of purchase requiredWhat you will learnDesign business-aligned AI strategiesSelect and prioritize AI projects with the highest potential ROIDevelop reliable prototypes and scale them using MLOps pipelinesIntegrate explainability, fairness, and compliance into AI systemsApply LLMOps practices to deploy and maintain generative AI modelsBuild AI agents that support autonomous decision-making at scaleNavigate evolving AI regulations with actionable compliance frameworksBuild a future-ready, ethically grounded AI organizationWho this book is forThis book is for AI/ML leaders and business leaders, CTOs, CIOs, CDAOs, and CAIOs, responsible for driving innovation, operational efficiency, and risk mitigation through artificial intelligence. You should have familiarity with enterprise technology and the fundamentals of AI solution development.

Paperback. Condition: New. Deliver measurable business value by applying strategic, technical, and ethical frameworks to AI initiatives at scaleFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI strategies that align with business goals and maximize ROIImplement enterprise-ready frameworks for MLOps, LLMOps, and Responsible AILearn from real-world case studies spanning industries and AI maturity levelsBook DescriptionAI is only as valuable as the business outcomes it enables, and this hands-on guide shows you how to make that happen. Whether you're a technology leader launching your first AI use case or scaling production systems, you need a clear path from innovation to impact. That means aligning your AI initiatives with enterprise strategy, operational readiness, and responsible practices, and The AI Optimization Playbook gives you the clarity, structure, and insight you need to succeed.Through actionable guidance and real-world examples, you'll learn how to build high-impact AI strategies, evaluate projects based on ROI, secure executive sponsorship, and transition prototypes into production-grade systems. You'll also explore MLOps and LLMOps practices that ensure scalability, reliability, and governance across the AI lifecycle.But deployment is just the beginning. This book goes further to address the crucial need for Responsible AI through frameworks, compliance strategies, and transparency techniques. Written by AI experts and industry leaders, this playbook combines technical fluency with strategic perspective to bridge the business-technology divide so you can confidently lead AI transformation across the enterprise.*Email sign-up and proof of purchase requiredWhat you will learnDesign business-aligned AI strategiesSelect and prioritize AI projects with the highest potential ROIDevelop reliable prototypes and scale them using MLOps pipelinesIntegrate explainability, fairness, and compliance into AI systemsApply LLMOps practices to deploy and maintain generative AI modelsBuild AI agents that support autonomous decision-making at scaleNavigate evolving AI regulations with actionable compliance frameworksBuild a future-ready, ethically grounded AI organizationWho this book is forThis book is for AI/ML leaders and business leaders, CTOs, CIOs, CDAOs, and CAIOs, responsible for driving innovation, operational efficiency, and risk mitigation through artificial intelligence. You should have familiarity with enterprise technology and the fundamentals of AI solution development.

Paperback. Condition: New. Deliver measurable business value by applying strategic, technical, and ethical frameworks to AI initiatives at scaleFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild AI strategies that align with business goals and maximize ROIImplement enterprise-ready frameworks for MLOps, LLMOps, and Responsible AILearn from real-world case studies spanning industries and AI maturity levelsBook DescriptionAI is only as valuable as the business outcomes it enables, and this hands-on guide shows you how to make that happen. Whether you're a technology leader launching your first AI use case or scaling production systems, you need a clear path from innovation to impact. That means aligning your AI initiatives with enterprise strategy, operational readiness, and responsible practices, and The AI Optimization Playbook gives you the clarity, structure, and insight you need to succeed.Through actionable guidance and real-world examples, you'll learn how to build high-impact AI strategies, evaluate projects based on ROI, secure executive sponsorship, and transition prototypes into production-grade systems. You'll also explore MLOps and LLMOps practices that ensure scalability, reliability, and governance across the AI lifecycle.But deployment is just the beginning. This book goes further to address the crucial need for Responsible AI through frameworks, compliance strategies, and transparency techniques. Written by AI experts and industry leaders, this playbook combines technical fluency with strategic perspective to bridge the business-technology divide so you can confidently lead AI transformation across the enterprise.*Email sign-up and proof of purchase requiredWhat you will learnDesign business-aligned AI strategiesSelect and prioritize AI projects with the highest potential ROIDevelop reliable prototypes and scale them using MLOps pipelinesIntegrate explainability, fairness, and compliance into AI systemsApply LLMOps practices to deploy and maintain generative AI modelsBuild AI agents that support autonomous decision-making at scaleNavigate evolving AI regulations with actionable compliance frameworksBuild a future-ready, ethically grounded AI organizationWho this book is forThis book is for AI/ML leaders and business leaders, CTOs, CIOs, CDAOs, and CAIOs, responsible for driving innovation, operational efficiency, and risk mitigation through artificial intelligence. You should have familiarity with enterprise technology and the fundamentals of AI solution development.

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