ML.NET Survey: Model Explainability

Jessie Houghton

Jessie

Model Explainability ensures you can debug or audit your machine learning models. By understanding how and why your model reacts in certain situations, you can ensure reliability and robustness, while avoiding bias.

Tell us about how you want to interpret your models and assess bias in ML.NET by taking this ~10 minute survey.

At the end, you can optionally leave your contact information if you’d like to talk with the ML.NET team about your Model Explainability and Fairness feedback.

ML.NET Survey: Model Explainability

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