CIS 490: Machine Learning - spring

Prereq: CIS 360; C or Better

General Education requirement: Natural Science Technology

Machine learning methods and applications. The course focuses on models and algorithms that learn from data. It examines how machine learning pipelines are designed and implemented, including dataset exploration, data preparation, feature engineering, model selection, training, evaluation, tuning, and deployment. Key algorithms are presented, including decision trees, artificial neural networks, k-nearest neighbors, regression, and Bayesian methods. Both supervised and unsupervised learning techniques are examined through practical applications.