Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning Solutions is a helpful resource for professionals and companies wishing to embrace emerging AI (artificial intelligence) trends such as generative AI and ML (machine learning) in the cloud. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. It offers everything you need to build large-scale, real-world corporate AI systems in the cloud utilizing an AI-First strategy. The book steps you through the process of integrating your operations with cutting-edge AI and ML solutions. The author shows you how to start an enterprise-wide AI transformation effort, all the way through setting up the machine learning end-to-end architecture, with clearly defined steps, numerous examples, and hands-on exercises. Its an indispensable reference, providing: A comprehensive approach to implementing large-scale, real-world corporate AI systems in the cloud, using an AI-First strategy to drive innovation Coverage of emerging AI/ML use cases, such as AI/ML in the edge, ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, democratizing of AI/ML, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Explanations of the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google cloud platforms Practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Expert guidance on selecting the ideal cloud platform, evaluating AI/ML cloud services, building a robust AI cloud platform, integrating the cloud with apps and systems Leading best practices on optimizing cloud infrastructure for scalability and automated operations through MLOps (Machine Learning Operations) Real-world guidance on deploying AI responsibly and ethically with an AI governance framework that ensures maximum transparency and accountability. Several practical learning and real-world examples to reinforce learning. Review questions and answers at the end of every chapter to help the reader assess their understanding of the concepts. Whether youre a beginner or an experienced AI or MLOps engineer, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. This book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.

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