This course provides the fundamentals of machine learning and deep learning techniques. Topics include some mathematical basis of machine learning, linear models for regression and classification, kernel methods (support vector machine), neural networks and deep neural networks, with focuses on model structure and model training/parameter estimation techniques. A course project with applications is required.
This course provides the fundamentals of machine learning and deep learning techniques. Topics include some mathematical basis of machine learning, linear models for regression and classification, kernel methods (support vector machine), neural networks and deep neural networks, with focuses on model structure and model training/parameter estimation techniques. A course project with applications is required.
