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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

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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 - 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:
The widespread of solutions powered by generative AI and large language models has led to a surge in the demand for machine learning engineers capable of building, managing, and scaling complex Gen AI-powered applications and systems.
This book starts by introducing relevant concepts such as Machine Learning Engineering, Generative AI, Large Language Models (LLMs), and MLOps. As you progress through each of the chapters of the book, you will learn how to leverage these concepts as well as various AWS services and solutions to build, manage, and optimize machine learning systems. In addition to this, you'll discover how to automate the LLMOps pipeline, optimize deep learning experiments, and make use of proven deployment strategies when dealing with LLMs. You'll also learn how to create Gen AI applications powered by retrieval-augmented generation (RAG). To help expand your knowledge and elevate your expertise on machine learning engineering, each chapter includes practical examples and clear explanations to help you manage, troubleshoot, and optimize Generative AI 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 experience and confidence needed for solving a wide variety of ML engineering challenges and 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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