MSCS 505N - Machine Learning

4 Credits

This course provides a broad introduction to automated learning from data. Machine learning is the
name given to the collection of techniques that allow computational systems to adaptively improve
their performance by learning from past observed data. The course introduces the theoretical
underpinnings of learning from data, the study of learning algorithms, as well as machine learning
applications. Topics include: supervised and unsupervised learning (including linear models, support
vector machines, decision trees, PCA, perceptron and neural networks) , regularization methods,
validation and model selection. An introduction to reinforcement learning will be included.