Machine Learning Security Operations at One of the World's Largest Brewing Companies

Explore machine learning security operations at one of the world's largest brewing companies in this GOTO Amsterdam 2022 conference talk. Delve into the parallels between MLSecOps and DevSecOps, focusing on Heineken's approach to automating security in their machine learning processes. Learn about data democratization, the machine learning operations lifecycle, shift-left security, and the concept of MLSecOps. Examine real-world use cases comparing secure and insecure ML workbenches, and understand the importance of security in leveraging big data for actionable insights. Gain knowledge on tools like Sonatype Nexus and their role in securing ML operations. Perfect for data scientists, ML engineers, and security professionals interested in implementing robust security measures in machine learning workflows within large-scale industrial settings.

Intro
Data democratization
MLOps: Machine learning operations
Machine learning operations life cycle
Shift-left security
What is MLSecOps?
Use case: Secure ML workbench
Use case: Insecure ML workbench
Quiz
Security importance
Sonatype Nexus
Use case: Secure ML workbench
Conclusion
Outro