Overview / Usage

Has over fifteen easy to understand notebooks on L1 vs L2 regression. Understanding basic algos like GBM, SVM, K means clusters, Naive Bayes, XGB and Random forest. How to use Word2vec for NLP. Dimensionality reduction like PCA and t-sne. Performance matrices like P-R curve and F-1 scores. Recomendation engines,time-series predictions using ARMA. Neural Nets concepts like CNN and RNN.