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590 FolgenJoin us to hear about our strategy for driving machine learning innovation for our customers and learn what's new from AWS in the machine learning space. Swami Sivasubramanian, VP of Amazon Machine Learning, will discuss and demonstrate the latest new services for ML on AWS: Amazon SageMaker, AWS DeepLens, Amazon Rekogntion Video, Amazon Translate, Amazon Transcribe, and Amazon Comprehend. Attend this session to understand how to make the most of machine learning in the cloud.
AWS has launched Amazon Sumerian. Sumerian lets you create and run virtual reality (VR), augmented reality (AR), and 3D applications quickly and easily without requiring any specialized programming or 3D graphics expertise. In this session, we will dive deep into details about Sumerian so you can see what's under the hood. We will cover creating a project, using the visual state machine, connecting an Amazon Sumerian scene to AWS services, and using a Sumerian Host to add presence to your applications.
AWS has launched Amazon Sumerian. Sumerian lets you create and run virtual reality (VR), augmented reality (AR), and 3D applications quickly and easily without requiring any specialized programming or 3D graphics expertise. In this session, we will introduce you to Sumerian, and how you can build highly immersive and interactive scenes for the enterprise that run on popular hardware such as Oculus Rift, HTC Vive, and iOS mobile devices.
Databases continue to grow to be multiple terabytes in size, but migrating to the cloud doesn't have to take days or create disruption for your business. To perform data migration at petabyte scale with minimal impact to your business, you can now use the new combination of AWS Database Migration Service replication agents and AWS Snowball. In this session, we discuss how to extract large-scale data from an on-premises Oracle database and migrate it to Amazon Aurora. We then outline a step-by-step process for converting your Oracle schema to a PostgreSQL-based schema.
In this session, Reza Zadeh, CEO of Matroid, presents a Kubernetes deployment on Amazon Web Services that provides customized computer vision to a large number of users. Reza offers an overview of Matroid's pipeline and demonstrates how to customize computer vision neural network models in the browser, followed by building, training, and visualizing TensorFlow models, which are provided at scale to monitor video streams.
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