Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively
Most companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies.
You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process.
By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.
This book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.
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Kieran Kavanagh is a Principal Architect at Google Cloud, working with Google's largest retail customers and driving some of the industry's most challenging digital transformation and generative AI initiatives. Before joining Google, he was a Principal AI/ML Solutions Architect in Strategic Accounts at Amazon Web Services (AWS), building some of the most complex AI/ML systems in the world. He was also a Principal Architect at AT&T, leading their Mobile Internet infrastructure design, and he is a public speaker on the topics of AI/ML, MLOps, and large-scale cloud transformation. Originally from Cork, Ireland, he now lives in Atlanta, GA, with his wife, Katelyn.
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