Machine Learning Basics

Deep Learning; basic architectures (MLP, RNN, LSTM, GRU, ResNet), regularizers, and normalization
Machine Learning; tree based (Decision Trees, Random Forest, GBM), bayesian techniques, linear families, and kernel methods

Table of Contents