sagemaker aws
In this demo, we show how to build a smart ad display to serve relevant advertisements in real-time, based on the inference from the audience looking at the ads. Advertising displays serve static or periodically shuffling ads, which change at…
Machine learned models and data-driven systems are being increasingly used to help make decisions in application domains such as financial services, healthcare, education, and human resources. With the goal that a significant portion of these decision systems becoming fully-automated, there…
Amazon FSx for Lustre is a high-performance file system for processing Amazon S3 or on-premises data. Learn more at - https://amzn.to/2GglrJa. With Amazon FSx for Lustre, you can launch and run a Lustre file system that can process massive data…
In this session, learn more about Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that helps developers operate machine learning (ML) models on a fleet of edge devices and solve challenges with constraints and maintenance of ML models…
Insufficient enterprise AI adoption often happens due to lack of time, data, and skills required to develop ML models for solving your business problems. In this session, learn how pretrained ML models which is available in AWS Marketplace and deployed…
AWS offers many choices for solving business problems through machine learning (ML), ranging from built-in algorithms to frameworks and more in using ML services. Amazon SageMaker supports the different built-in ML algorithms, such as classification, regression, and recommendation. Built-in algorithms…
