Regularization is a set of techniques which can help avoid overfitting in neural networks, thereby improving the accuracy of deep learning models when it is fed entirely new data from the problem domain. There are various regularization techniques, some of the most popular ones are — L1, L2, dropout, early stopping, and data augmentation. Why…

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