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Can I read The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS on EtoBox?

The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS by Neel Sendas, Deepali Rajale is a nonfiction available to read on EtoBox.

What is The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS about?

Foreword by Dr. Shreyas Subramanian, Principal Data Scientist, AmazonThis book focuses on deploying, testing, monitoring, and automating ML systems in production. It covers AWS MLOPS tools like Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS.This book explains how to design, develop, and deploy ML workloads at scale using AWS cloud's well-architected pillars. It starts with an introduction to AWS services and MLOps tools, setting up the MLOps environment. It covers operational excellence, including CI/CD pipelines and Infrastructure as code. Security in MLOps, data privacy, IAM, and reliability with automated testing are discussed. Performance efficiency and cost optimization, like Right-sizing ML resources, are explored. The book concludes with MLOps best practices, MLOPS for GenAI, emerging trends, and future developments in MLOpsBy the end, readers will learn operating ML workloads on the AWS cloud. This book suits software developers, ML engineers, DevOps engineers, architects, and team leaders aspiring to be MLOps professionals on AWS.What you will learn● Create repeatable training workflows to accelerate model

Who reads The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Neel Sendas, Deepali Rajale
Publisher
Apress
Published
2024
Language
EN
ISBN
9798868810763
Category
nonfiction
Subjects
Computer Science, Artificial Intelligence (Ai), Stem

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