L1 Regularization, L2 Regularization, Regularization, Early Stopping, Dropout.
Overfitting occurs when a model learns not only the underlying patterns in the training data but also the noise. As a result, it performs exceptionally well on the training data but poorly on new, unseen data. Imagine memorizing a textbook instead of understanding the concepts; that’s the deep