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Google Machine Learning and Generative AI for Solutions Architects

Google Machine Learning and Generative AI for Solutions Architects

By : Kieran Kavanagh
4.9 (7)
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Google Machine Learning and Generative AI for Solutions Architects

Google Machine Learning and Generative AI for Solutions Architects

4.9 (7)
By: Kieran Kavanagh

Overview of this book

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.
Table of Contents (24 chapters)
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1
Part 1:The Basics
5
Part 2:Diving in and building AI/ML solutions
17
Part 3:Generative AI

Google Cloud Vertex AI

This is where we start getting to expert-level AI/ML. Think back on all of the data science concepts we’ve covered so far in this book; all of the different types of ML approaches, algorithms, use cases, and tasks. Vertex AI is where you can accomplish all of them, and many more that we will yet explore in this book. You can use Vertex AI as your central command center for performing everything AI/ML-related. Our ML model lifecycle diagram in Figure 3.14 illustrates this point graphically. Traditionally, we would expect an AI/ML platform to mainly take care of training, evaluating, deploying, and monitoring models. This is what’s represented by the blue box on the right-hand side of Figure 3.14, and all of these activities are of course supported by Vertex AI. However, with additional features such as notebooks and MLOps pipelines, Vertex goes beyond just those traditional ML activities, to also enable us to perform all of the tasks in our lifecycle...

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Google Machine Learning and Generative AI for Solutions Architects
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