Sergios Theodoridis

P3.10-SVM- The Hinge Loss Function

P4.1a-Perceptron Follow Up

P4.1-Perceptron

P4.2-Feed Forward NNs

P4.3-Training NNs

P4.4-The Backpropagation Algorithm

P4.5-Variants of the Gradient Descent Scheme

P4.6-Batch Normalization

P4.7-Loss Function Selection and the Softmax Activation Function

P4.8-ReLU Activation Function

P4.9-Regularization and Dropout

P4.10-Universal Approximation Property and Deep Networks