Applied Machine Learning

Catalog description

Machine Learning is the basis for the most exciting careers in data analysis today. This course introduces students to the concepts of machine learning and deep learning. This course covers a broad introduction to machine learning techniques, which include both supervised learning and unsupervised learning techniques such as classification, support vector machines, decision trees, ensemble learning and random forests, dimensionality reduction, and neural networks and deep learning. In addition to learning about the most effective machine learning techniques, you will gain the practical implementation of applying these techniques to real engineering problems.