CSCI 3345 Machine Learning (Spring: 3 )
This course provides an introduction to the field of machine learning. Specific learning paradigms to be covered include decision trees, neural networks, genetic algorithms, probabilistic models, and instance-based learning. General concepts include supervised and unsupervised adaptation, inductive bias, generalization, and fundamental tradeoffs. Applications to areas such as human-machine interaction, machine vision, bioinformatics, and computational science will be discussed.
Instructor(s): Sergio Alvarez
Last Updated: 24-Jun-17