Evaluating Real-World Adversarial ML Attack Risks and Effective Management: Robustness vs Non-ML Mitigations
The MLSecOps Podcast
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Building Effective Machine Learning Models with Clear Goals
The speakers discuss the importance of understanding the fundamental goals of a machine learning model, highlighting the need to not just focus on accuracy and robustness. They provide an example of fraud detection and emphasize the importance of building models that effectively help achieve desired goals.
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