IT461 - Practical Machine Learning

Practical machine learning will introduce the fundamental concepts and algorithms that enable
computers to learn from experience, with an emphasis on their practical application to real problems.
This course will introduce supervised learning such as linear regression, logistic regression,
support vector machines, Perception, Neural Network, NN optimization, Recurrent Neural Networks,
ensembles. Unsupervised learning such as (clustering, dimensionality reduction) and
recommender system. Additionally, the course will discuss evaluation methodology and recent
applications of machine learning.