INF552 Machine Learning

Decision Trees

Implemented Decision Tree Learning Algorithm for classification.

K-Means and Gaussian Mixture Model (GMM)

Implemented K-Means Algorithm and Gaussian Mixture Model (GMM) using Expectation Maximization Algorithm for clustering.

PCA and FastMap

Implemented Principal Component Analysis (PCA) to reduce the dimensionality of data points from 3D to 2D. Implemented FastMap Algorithm to embed objects (word vectors) into a 2D space.

Perceptron Learning and Regression

Implemented Perceptron Learning Algorithm, Pocket Algorithm, Logistic Regression, and Linear Regression for classification.

Neural Networks

Implemented Back Propagation Algorithm for Feed Forward Neural Networks for gesture recognition.

Support Vector Machines

Implemented Support Vector Machines (SVM) for both linear and nonlinear data classification using Quadratic Programming with polynomial kernel function.

Hidden Markov Models (HMM)

Implemented Hidden Markov Models (HMM) using Viterbi Algorithm to predict the trajectory of a robot in a given grid world.