Securing Machine Learning Resources on AWS

Explore comprehensive security strategies for machine learning workloads in this 56-minute conference talk from AWS re:Invent 2025. Discover best practices for protecting ML resources through robust security controls, including implementing effective IAM policies, configuring secure network architectures, and building reliable CI/CD pipelines specifically designed for ML workflows. Gain insights through practical demonstrations and real-world examples that showcase how to effectively safeguard sensitive machine learning workloads using AWS services. Learn essential security techniques that data scientists, ML engineers, and security professionals need to enhance their ML security expertise and protect their cloud-based machine learning infrastructure.