MACHINE LEARNING MODELS IN PYTHON

Catalog description

Prerequisites: MAT 126, MAT 311, CIS 512, or Instructor Permission. Applied introduction to building predictive, machine-learning models for real-world problems; learning Python computing environment, basic data analysis, management; data visualization and reporting using machine learning methods, including k-nearest neighbor, linear models, naïve Bayesian models, decision trees, random forests, and neural networks. Sample data sets from across industry professions. Offered occasionally.