The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS | Agenda Bookshop Skip to content
Selected Colleen Hoover Books at €9.99c | In-store & Online
Selected Colleen Hoover Books at €9.99c | In-store & Online
A01=Deepali Rajale
A01=Neel Sendas
Age Group_Uncategorized
Age Group_Uncategorized
Author_Deepali Rajale
Author_Neel Sendas
automatic-update
Category1=Non-Fiction
Category=KJMV
Category=UTC
Category=UYQ
COP=Germany
Delivery_Pre-order
Language_English
PA=Not yet available
Price_€50 to €100
PS=Forthcoming
softlaunch

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

English

By (author): Deepali Rajale Neel Sendas

This 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 MLOps

 

By 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 development

Catalog ML artifacts centrally for model reproducibility and governance

Integrate ML workflows with CI/CD pipelines for faster time to production

Continuously monitor data and models in production to maintain quality

Optimize model deployment for performance and cost

 

Who this book is for:

This book suits ML engineers, DevOps engineers, software developers, architects, and team leaders aspiring to be MLOps professionals on AWS.

 

 

See more
Current price €61.19
Original price €67.99
Save 10%
A01=Deepali RajaleA01=Neel SendasAge Group_UncategorizedAuthor_Deepali RajaleAuthor_Neel Sendasautomatic-updateCategory1=Non-FictionCategory=KJMVCategory=UTCCategory=UYQCOP=GermanyDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€50 to €100PS=Forthcomingsoftlaunch

Will deliver when available. Publication date 31 Dec 2024

Product Details
  • Dimensions: 178 x 254mm
  • Publication Date: 31 Dec 2024
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Publication City/Country: Germany
  • Language: English
  • ISBN13: 9798868810756

About Deepali RajaleNeel Sendas

Neel Sendas is a Principal Technical Account Manager at Amazon Web Services (AWS). In this role he serves as the AWS Cloud Operations lead for some of the largest enterprises that utilize AWS services. Drawing from his expertise in cloud operations in this book Neel presents solutions to common challenges related to ML Cloud Governance Cloud Finance and Cloud Operational Resilience & Management at scale. Neel also plays a crucial role as part of the core team of Machine Learning Technical Field Community leaders at AWS where he contributes to shaping the roadmap of AWS Artificial Intelligence and Machine Learning (AI/ML) Services. Neel is based in the state of Georgia United States.   Deepali Rajale is a former AWS ML Specialist Technical Account Manager with extensive experience supporting enterprise customers in implementing MLOps best practices across various industries. She is also the founder of Karini AI a company dedicated to democratizing generative AI for businesses. She enjoys blogging about ML and Generative AI and coaching customers to optimize their AI/ML workloads for operational efficiency and cost optimization. In her spare time she enjoys traveling seeking new experiences and keeping up with the latest technology trends.    

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept