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Machine Learning Engineering on AWS. Build, operationalize, optimize, and secure Generative AI systems and LLMOps workflows in production - Second Edition Joshua Arvin Lat

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Machine Learning Engineering on AWS. Build, operationalize, optimize, and secure Generative AI systems and LLMOps workflows in production - Second Edition Joshua Arvin Lat - okladka książki

Machine Learning Engineering on AWS. Build, operationalize, optimize, and secure Generative AI systems and LLMOps workflows in production - Second Edition Joshua Arvin Lat - okladka książki

Autor:
Joshua Arvin Lat
Serie wydawnicze:
Hands-on
Ocena:
The recent advancements in generative AI, large language models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents have accelerated the demand for machine learning engineers capable of building, managing, and scaling modern AI-powered systems. As the landscape of AI rapidly evolves, staying ahead requires a deep understanding of the relevant concepts as well as the practical tools, services, and platforms needed to implement them effectively.
With this hands-on book, you will discover how to leverage various AWS services such as Amazon Bedrock and the next generation of Amazon SageMaker to build, optimize, and manage production-ready machine learning (ML) systems. You will learn how to build RAG-powered Generative AI applications, automate LLMOps workflows, build reliable and responsible AI agents, optimize a managed transactional data lake, and make use of proven deployment and evaluation strategies when dealing with various models. To help elevate your expertise on ML engineering, each chapter includes practical examples and clear explanations to help you manage, troubleshoot, and optimize ML systems running on AWS.
By the end of this book, you'll be able to operationalize and secure Generative AI applications on AWS, which will give you the confidence needed to solve a wide variety of ML engineering requirements.

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O autorze książki

Joshua Arvin Lat is the Chief Technology Officer (CTO) of NuWorks Interactive Labs, Inc. He previously served as the CTO of three Australian-owned companies and also served as the Director for Software Development and Engineering for multiple e-commerce start-ups in the past, which allowed him to be more effective as a leader. Years ago, he and his team won first place in a global cybersecurity competition with their published research paper. He is also an AWS Machine Learning Hero and has shared his knowledge at several international conferences, discussing practical strategies on machine learning, engineering, security, and management.

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