Google Machine Learning and Generative AI for Solutions Architects

by Kieran Kavanagh

​Learn how to architect and run real-world AI/ML solutions at scale on Google Cloud, as well as best practices, common industry challenges, and how to address those challenges effectively. Almost every company nowadays is either using or trying to use AI/ML in some way. While AI/ML research is undoubtedly complex, what is often more complex is actually building and running applications that use AI/ML effectively. This book teaches you how to successfully design and run AI/ML workloads, based on years of experience implementing large-scale and highly complex AI/ML projects at some of the world’s leading technology companies. ​Understand the common challenges that companies run into when implementing AI/ML workloads, and industry-proven best practices to overcome those challenges. Learn about the vast AI/ML landscape on Google Cloud and how to implement all of the required steps in a typical AI/ML project. Use services such as BigQuery to prepare data, and Vertex AI to train, deploy, monitor, and scale models in production, as well as MLOps to automate the entire process. ​Suitable both for beginners and experienced practitioners, it begins by covering important fundamental AI/ML concepts, and then builds in complexity through examples and hands-on activities to eventually dive deep into advanced, cutting-edge AI/ML applications that address real-world use-cases in today’s market. People aspiring to become Solution Architects, who want to know how to design and implement AI/ML solutions on Google Cloud. Basic knowledge of Python and ML concept required. This book will briefly cover the basics at the beginning in order to establish a baseline for the readers, but it will not go into depth on the underlying mathematical concepts that the readers could learn from academic materials. It will focus on how to use AI/ML in the real world on Google Cloud

552 pages, Paperback

Published June 28, 2024