Explore the emerging field of MLSecOps and learn how to integrate security measures throughout the machine learning model lifecycle in this 47-minute conference talk from MLOps World. Discover the importance of shifting security considerations left in the development process to address threats before models reach production. Gain insights into vital elements of MLSecOps, practical implementation strategies, and best practices for effective risk management in machine learning projects. Understand how this approach helps address security vulnerabilities, privacy issues, and regulatory compliance early on. Learn from Arun Prabhakar, a Senior Consultant at Security Compass, as he shares his expertise in secure system development and emerging technologies like machine learning, blockchain, and IoT.
MLSecOps and Shift-Left Security in Machine Learning Model Lifecycle
MLOps World: Machine Learning in Production via YouTube
Overview
Syllabus
MLSecOps and Shift-left your security gears in Model Lifecycle
Taught by
MLOps World: Machine Learning in Production
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