Machine Learning

Catalog description

This course is meant to introduce students to machine learning and deep learning. ME 107 is taught at the undergraduate level and teaches students how to identify a machine learning problem in the context of real-world applications, mathematically formulate a learning problem, identify when a learning problem is well-posed, under-determined and overdetermined, and develop algorithms and Python code to solve the problem. Students are introduced to the concepts of learning algorithms, overfitting, under-fitting, statistical measures of estimators, optimization approaches to learning, principal component analysis, regression, support vector machines, and artificial neural networks.