CLOUD COMPUTING FOR AI

The journey through this book is structured to provide a progressive learning curve. I begin by laying the groundwork, exploring the fundamental principles of both Cloud Computing and Artificial Intelligence, and immediately delve into how these two domains intertwine. Subsequent chapters meticulously unpack the various cloud service models (IaaS, PaaS, SaaS) and their specific relevance to AI workloads. We then navigate through the critical aspects of data management, high-performance computing resources like GPUs and TPUs, and the pivotal role of specialized AI platforms-as-a-Service (AI PaaS) and MLOps in streamlining the AI development lifecycle.


Key Features:

1. NEP 2020 and AICTE Compliant: Structured to foster multidisciplinary learning, critical thinking, and practical skill development as envisioned by modern educational frameworks in India.
2. Global Syllabus Alignment: Content covers topics relevant to B.Tech/M.Tech AI and Cloud Computing courses in universities worldwide.
3. Comprehensive Coverage in 10 Chapters: Logically organized to cover all essential aspects from fundamentals to advanced topics, including cloud service models for AI, data management, compute resources, AI PaaS, MLOps, pre-trained AI services, serverless AI, edge AI, security, and ethics.
4. Updated and Latest Content: Incorporates the most recent advancements in cloud AI services, tools, and best practices from leading cloud providers.
5. Simplest and Easiest Examples: Complex concepts are explained using clear language and practical, easy-to-understand examples, facilitating better comprehension and retention.
6. Practical Application Focus: Emphasizes how to use cloud services (AWS, Azure, GCP examples) for real-world AI tasks like model training, deployment, and management.
7. MLOps and AI PaaS Deep Dive: Dedicated coverage of Machine Learning Operations (MLOps) and AI Platform-as-a-Service offerings, crucial for modern AI development workflows.
8. Ethical and Secure AI: Addresses the vital considerations of security, governance, bias, fairness, and responsible AI deployment in cloud environments.
9. Industry-Relevant Skills: Equips readers with the knowledge and skills highly sought after in the rapidly growing field of cloud-based AI.
10. Future-Oriented: Discusses emerging trends and future directions, preparing readers for the evolving landscape of AI and Cloud Computing.


This book aims to be an indispensable companion for anyone looking to navigate the exciting world of Artificial Intelligence powered by the scalability, flexibility, and innovation of Cloud Computing.