Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
module are: To learn different optimization methods such as (Stochastic) Gradient Descent, Momentum, RMSProp and Adam Using random mini batches to accelerate the convergence and improve the optimization To know the benefits of learning rate decay and apply it to your optimization Mini-Batch