marydwyer/mlfall2017

MLFall2017

This repository contains projects from ECE-414-1: Machine Learning course at The Cooper Union for the Advancement of Science and Art. The class was taught by Professor Sam Keene during the Fall of 2017.

Course Description

Machine learning of structural relationships among variables from empirical data. This course covers decision theory and Bayesian Machine Learning. Projects were conducted on:
Classification: linear discriminant analysis, support vector machines(SVM), boosting.
Regression: leastsquares,regularization methods,logistic regression.
Clustering: kmeans and EM algorithms.
Modelselection: bias-variance tradeoff, crossvalidation, over-fitting.
Feature selection and dimensionality reductionmethods including PCA, ICA, MDS, Kernel methods.