Debugging ML Models: Difference between revisions

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Notes on debugging ML models, primarilly CNNs.   
Notes on debugging ML models, primarilly CNNs.   
Most of this is advice I've found online or gotten through mentors.
Most of this is advice I've found online or gotten through mentors or experience.


==Debugging==
==Debugging==
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==Overfitting==
==Overfitting==
Overfitting occurs when your training loss is below your validation loss.   
Overfitting occurs when your model begins learning attributes specific to your training data, causing your validation loss to increase.   
Historically this was a big concern for ML models and people relied heavily on regularization to address overfitting.   
Historically this was a big concern for ML models and people relied heavily on regularization to address overfitting.   
Recently though, overfitting has become less of a concern with larger ML models.
Recently though, overfitting has become less of a concern with larger ML models.