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Model Deployment with Amazon SageMaker

Discover how to effectively deploy machine learning models using Amazon SageMaker. This course will teach you how to deploy, monitor, and optimize models in production, ensuring cost-effective and scalable solutions for your ML projects.

Bogdan Sucaciu - Pluralsight course - Model Deployment with Amazon SageMaker
by Bogdan Sucaciu

What you'll learn

Deploying machine learning models to production can be complex and challenging, often involving multiple tools and workflows. In this course, Model Deployment with Amazon SageMaker, you’ll learn to efficiently deploy and manage models in production. First, you’ll explore how to deploy models using SageMaker’s various tools and endpoints. Next, you’ll discover how to monitor, update, and manage these deployments. Finally, you’ll learn how to optimize costs and manage resources effectively. When you’re finished with this course, you’ll have the skills and knowledge to confidently deploy and maintain models using Amazon SageMaker.

Table of contents

About the author

Bogdan Sucaciu - Pluralsight course - Model Deployment with Amazon SageMaker
Bogdan Sucaciu

Bogdan Sucaciu is a Software Engineer at Axual in The Netherlands, where he is taking part in building a Streaming Platform designed to share information in real-time, enabling instant processing of incoming events. He has several years of experience "cooking" software with JVM-based languages, some flavors of web technologies and garnishing with automated testing.

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