CSCI 230 - Introduction to Machine Learning and Big Data

Credits: 3

Prerequisite: CSCI 112. This course is an intermediate-level computer science course that gives an overview of machine learning algorithms, concepts, and applications. We will begin with an understanding of how to systematically extract and prepare data for these types of models. We will explore common machine learning models such as linear regression, logistic regression, support vector machines, k-nearest neighbors, random forest, hidden Markov models, Bayesian networks, and others. Students will be exposed to how to train and evaluate the quality of their models. This evaluation includes a thorough investigation into whether the models present bias and what techniques can be employed to mitigate these limitations.