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loss functions

This project provides several implementations that can be used to analyze Hessians associated with synthetic and empirical loss functions.

Machine Learning Basics - implementation of: loss functions (cross entropy loss, L1 loss, L2 loss, hinge loss), regularizations (L1 regularizer, L2 regularizer, early stopping), gradient check, optimizers, training a simple deep model.