Secure Python ML - The Major Security Flaws in the ML Lifecycle and How to Avoid Them

This course covers the major security flaws in the machine learning lifecycle, providing insights on how to identify and mitigate these risks. Participants will learn about critical security risks in various phases of the ML lifecycle, along with practical examples and tools to address them. The teaching method involves a hands-on example of training, packaging, and deploying a model, highlighting key risk areas and security best practices. This course is designed for machine learning practitioners looking to enhance their understanding of security best practices in ML operations.