Wednesday, July 22
3:00 – 4:00 p.m.
On Zoom
The KAUST Machine Learning Hub seminar invites to you a talk entitled: “Amazon SageMaker Ground Truth” by Nitin Wagh, Sr. Business Development Manager, Amazon AI.
Learning objectives:
- Learn about Amazon SageMaker Ground Truth and how to build training datasets with high accuracy
- Learn how you can achieve automated labeling while reducing costs to address a range of use cases including 3D point clouds, video, images and text.
- Learn about Amazon SageMaker Ground Truth roadmap.
Abstract:
Successful machine learning models are built on the foundation of large volumes of high-quality training data. But the process to create the training data necessary to build these models is often expensive, complicated, and time-consuming. Amazon SageMaker Ground Truth significantly reduces the time and effort required to create datasets for training. SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks. As part of the workflows, labelers have access to assistive labeling features such as automatic 3D cuboid snapping, removal of distortion in 2D images and auto-segment tools to reduce the time required to label datasets. Join us and learn how to use Amazon SageMaker Ground Truth to build highly accurate training datasets for machine learning research projects.
KAUST Machine Learning Hub
http://ml.kaust.edu.sa/
