Google Machine Learning and Generative AI for Solutions Architects

eBook Details:

• Paperback: 552 pages
• Publisher: WOW! eBook (June 28, 2024)
• Language: English
• ISBN-10: 1803245271
• ISBN-13: 978-1803245270

eBook Description:

Google Machine Learning and Generative AI for Solutions Architects: ​Build efficient and scalable AI/ML solutions on Google Cloud. Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively.

Nearly all companies nowadays either already use or are trying to incorporate AI/ML into their businesses. While AI/ML research is undoubtedly complex, the building and running of apps that utilize AI/ML effectively is tougher. This Google Machine Learning and Generative AI for Solutions Architects book shows you exactly how to design and run AI/ML workloads successfully using years of experience some of the world’s leading tech companies have to offer.

You’ll begin by gaining a clear understanding of essential fundamental AI/ML concepts, before moving on to grasp complex topics with the help of examples and hands-on activities. This will help you eventually explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. As you advance, you’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these challenges. 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.

• Build solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and Spark
• Source, understand, and prepare data for ML workloads
• Build, train, and deploy ML models on Google Cloud
• Create an effective MLOps strategy and implement MLOps workloads on Google Cloud
• Discover common challenges in typical AI/ML projects and get solutions from experts
• Explore vector databases and their importance in Generative AI applications
• Uncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflows

By the end of this Google Machine Learning and Generative AI for Solutions Architects book, you will be able to unlock the full potential of Google Cloud’s AI/ML offerings.