Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...
Regularization aims to improve prediction performance by trading an increase in training error for better agreement between training and prediction errors, which is ...
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