Securing Machine Learning
Protecting systems that handle data is crucial, especially when it comes to validating incoming data and ensuring it meets expected distributions and types. Techniques like dimensionality reduction can help identify potential adversarial examples, while advancements in adversarial training show promise for improving model security. Treating machine learning API endpoints with the same caution as database endpoints is essential to prevent model theft and abusive behavior.In this clip
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Episode 395: Katharine Jarmul on Security and Privacy in Machine Learning
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