Broadcast Date: June 18, 2019
Cloud security at AWS is the highest priority. At AWS, building a secure environment from our data centers to our network architecture is of paramount importance. The same principles apply to machine learning where we provide a secure environment using our machine learning services and in particular Amazon SageMaker. In this tech talk, we will discuss how the features of Amazon SageMaker can be applied to build a secure ML environment, including the secure end points, the logging controls, the governance, and the compliance aspects. The talk will also cover the interaction of SageMaker with other AWS services to ensure the highest security for your machine learning models.
- Learn about building a secure machine learning environment using Amazon SageMaker
- Learn about the interaction of Amazon SageMaker with other AWS services to provide the highest cloud security
- Learn the features of Amazon SageMaker that help build robust and secure machine learning models
Who Should Attend?
Machine Learning Practitioners, Developers, Data Scientists, Technical Decision Makers, Architects
Service How To
December 19th, 2018 | 1:00 PM PT
Developing Deep Learning Models for Computer Vision with
Amazon EC2 P3 Instances.