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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

AI/ML Tooling and the Google Cloud AI/ML Landscape

In this chapter, we take a look at the various tools in Google Cloud that can be used to implement AI/ML workloads. We start off with a quick overview of some of the fundamental Google Cloud services that function as the building blocks for almost all workloads on Google Cloud. We then progress toward more advanced services that are used specifically for data science and AI/ML workloads. This is the final chapter in the Basics part of this book, and like the previous two chapters, it provides foundational information that we build upon throughout the book. If you already have knowledge of Google Cloud’s services, this chapter may serve as a refresher for that knowledge. If you are new to Google Cloud, this chapter is an essential part of your learning process, because it introduces concepts that are assumed to be known in the rest of the book.

To describe how each tool is used in the context of data science projects, we will...

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Google Machine Learning and Generative AI for Solutions Architects
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