CSC 572 Machine Learning

Machine Learning is one of the fastest growing areas in Computer Science. Machine Learning leverages the capabilities of today's computer hardware combined with domain specific data called sample data in order to build models (algorithms) to make predictions or decisions based on new data. This course is intended to provide an overview of machine learning concepts including both supervised and unsupervised learning. This course provides an in-depth look at several of the most common algorithms used in the machine learning including linear regression, logistic regression, neural networks, support vector machines, nearest neighbor, k-means, etc. These techniques can generate highly accurate algorithms without being explicitly programmed. A review of Linear Algebra and Python will be provided during the first week of the course. Students will use both Python and Octave to implement algorithms. Prerequisite: CSC 202 or CSC 522.

Credits

3