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I applied via Referral and was interviewed before Aug 2023. There was 1 interview round.
Overfitting occurs when a model learns the training data too well, leading to poor performance on new, unseen data.
Overfitting occurs when a model is too complex and captures noise in the training data.
It can be identified when a model performs well on training data but poorly on test data.
Techniques to prevent overfitting include cross-validation, regularization, and early stopping.
Example: A decision tree with too ma...
I applied via Referral and was interviewed before Aug 2023. There was 1 interview round.
Overfitting occurs when a model learns the training data too well, leading to poor performance on new, unseen data.
Overfitting occurs when a model is too complex and captures noise in the training data.
It can be identified when a model performs well on training data but poorly on test data.
Techniques to prevent overfitting include cross-validation, regularization, and early stopping.
Example: A decision tree with too ma...
I applied via Referral and was interviewed in Feb 2020. There were 5 interview rounds.
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