Regularization is a technique used in machine learning to prevent overfitting, which is a situation where a machine learning model performs well on training data but poorly on unseen data (test data).

The paper generated by The AI Scientist-v2 passed peer review at a workshop of a top international AI conference. The ...

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 ...