Build Models Faster, and Serve Predictions at Scale, using Amazon SageMaker Feature Store
Mark Roy from Amazon talks how SageMaker can help to accelerate the ML lifecycle, providing low-latency and high throughput inference.
Mark Roy from Amazon talks how SageMaker can help to accelerate the ML lifecycle, providing low-latency and high throughput inference.
ML has quickly become a top priority for organizations everywhere, but achieving ML at scale across many business units and teams is no small feat. Join this session to learn how Amazon SageMaker Feature Store lets you share ML features, search for and discover existing features, and flexibly reuse features in new models to accelerate the pace of ML model development. Come learn how SageMaker is helping data scientists and ML engineers accelerate the ML lifecycle, while providing low-latency and high throughput inference.