• Implemented a k-Nearest Neighbor classifier, Perceptron algorithm and Linear Regression and evaluate them.
• Implemened Logistic Regression for binary and multiclass classification. • Built multi-layer perceptrons and convolutional neural networks.
• Built a linear SVM classifier and decision tree classifier. • Implemented Decision Stump, AdaBoost and Logitboost Algorithms.
• Implemented K-means clustering algorithms and used K-means clustering to classify data and compress image. • Implemented EM algorithms to estimate the parameters of Gaussian Mixture Models and to sample from the GMM distribution.
• Implement three inference procedures of of a small hidden Markov model. • Implement Principal Component Analysis (PCA) and use it for image compression.