Kate Zimmerman

In this session, learn how Poshmark is focusing on achieving top-line growth through personalization and enhanced user experience. The initial approach of using batch processing for personalization and security did not meet expectations for customer experience improvement.

The rise in commercial remote sensing capabilities from space has opened the door to a new level of persistent activity monitoring around the world, especially in the maritime domain. In this session, learn from HawkEye 360 about how radio frequency data can be fused with multi-source data sets, using cloud technologies like Amazon SageMaker, AWS Lake Formation, and Amazon EKS to create highly...

Join this session to learn about AutoML on AWS and to get an overview of the AWS options for AutoML, including AutoGluon, an open-source library for AutoML. Also, learn how to use Amazon SageMaker Autopilot to automatically build the best machine learning (ML) model based on your dataset.

This session covers how to use Amazon SageMaker Autopilot to automatically build the best machine learning (ML) model for your data and interpret your model’s predictions with just a few clicks. Amazon SageMaker Autopilot automatically trains and tunes hundreds of ML models to optimize your success metric and creates the model that best suits your data.

Capella Space is leveraging Amazon SageMaker to build complex machine learning (ML) models on Synthetic Aperture Radar (SAR) satellite imagery. By applying ML to SAR imagery, Capella can begin automatically detecting global events in near-real time without being hindered by weather or time of day.