AIM327-R1: Security for ML environments w/ Amazon SageMaker, featuring Vanguard - a podcast by AWS

Amazon SageMaker is a modular, fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. In this session, we dive deep into the security configurations of Amazon SageMaker components, including notebooks, training, and hosting endpoints. A representative from Vanguard joins us to discuss the company's use of Amazon SageMaker and its implementation of key controls in a highly regulated environment, including fine-grained access control, end-to-end encryption in transit, encryption at rest with customer master keys (CMKs), private connectivity to all Amazon SageMaker API operations, and comprehensive audit trails for resource and data access. If you want to build secure ML environments, this session is for you.

Further episodes of AWS re:Invent 2019

Further podcasts by AWS

Website of AWS