Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
requisite data due to various reasons. In such cases, we can use data augmentation, i.e., applying some changes such as flipping the image, taking random crops of the image, randomly rotating images, etc. These can potentially help us get more training data and hence reduce overfitting. Early