Machine Learning in Business Decision Making

Catalog description

Provides a comprehensive understanding of applied machine learning concepts and relevant open-source tools in the business sector. Investigates data manipulation and the creation of advanced models, covering regressors, classifiers, and meta-stacked models like gradient boosting, support vector machines, multi-layer perceptron, and ensembled stacked models. Introduces dimension reduction techniques like PCA and automates feature selection using methods such as Boruta. Converts complex data into actionable insights, cultivating essential decision-making skills for success in dynamic business environments. Enrollment Restrictions: Enrollment is restricted to students in the Master of Science in Business Analytics program.