MachineLearning

MachineLearning

Implemented this as a part of Machine Learning Course( CS 6375 ) by Prof. Nicholas Ruozzi at University of Texas at Dallas(UTD).

Implemented Different Machine Learning Models like

1) Gradient Descent ( Linear Regression )
2) Stochastic Gradient Descent
3) Support Vector Machine (Quadratic Programming) for Binary Classification
4) Decision Trees for Classification
5) Bagging
6) Boosting
7) Dual SVM with Slack
8) Primal slack
9) K-Nearest Neighbours
10) K-Means Clustering
11) Spectral Clustering
12) Naive Bayes used for Classification
13) Naive Bayes with Sampling a Probability Distribution
14) Mixture Models