IT461: Practical Machine Learning

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