Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
sets from the given data. We will also be covering topics like regularization, dropout, normalization, etc. that help us make our model more efficient. In module 2, we will discuss the concept of a mini-batch gradient descent and a few more optimizers like Momentum, RMSprop, and ADAM. In the last