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Machine Learning Engineering on AWS. Operationalize and optimize generative AI systems and LLMOps pipelines in production - Second Edition Joshua Arvin Lat

Język publikacji: angielskim
Machine Learning Engineering on AWS. Operationalize and optimize generative AI systems and LLMOps pipelines in production - Second Edition Joshua Arvin Lat - okladka książki

Machine Learning Engineering on AWS. Operationalize and optimize generative AI systems and LLMOps pipelines in production - Second Edition Joshua Arvin Lat - okladka książki

Autor:
Joshua Arvin Lat
Serie wydawnicze:
Hands-on
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Recent advancements in generative AI, large language models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents have created a soaring demand for machine learning engineers who can build, manage, and scale modern AI-powered systems. To stay ahead in this rapidly evolving AI landscape, you need a deep theoretical understanding as well as hands-on expertise with the right tools, services, and platforms.
Machine Learning Engineering on AWS is a practical guide that teaches you how to harness AWS services such as Amazon Bedrock and the next generation of Amazon SageMaker to build, optimize, and manage production-ready ML systems. You’ll learn how to build RAG-powered GenAI applications, automate LLMOps workflows, develop reliable and responsible AI agents, and optimize a managed transactional data lake. The book also covers proven deployment and evaluation strategies for dealing with various models, along with practical examples to help you manage, troubleshoot, and optimize ML systems running on AWS.
Guided by AWS Machine Learning Hero Joshua Arvin Lat, you’ll be able to grasp complex ML concepts with clarity and gain the confidence to operationalize and secure GenAI applications on AWS to meet 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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