CSCI-567-Machine-Learning

This repo includes my solutions to the assignments of CSCI-567 Machine Learning course in University of Southern California taught by Prof. Sha.

Code structure

• ./homework1/: contains code for the implementation of linear regression, k-nearest neighbors, and logistic regression.
• ./homework2/: contains code for the implementation of multi-class classification,, multi-layer perceptrons (MLPs), and convolutional neural networks (CNNs).
• ./homework3/: contains code for the implementation of support vector machines (SVM).
• ./homework4/: contains code for the implementation of K-means, Gaussian mixture models (GMMs), and Naive Bayes.
• ./homework5/: contains code for the implementation of hidden Markov models (HMMs), PCA and t-SNE for dimensionality reduction.