COM 3920: Machine Learning

Abstract

Description Machine learning's goal is to develop applications whose accuracy in predicting the value of unknown data improves by examining more and more known data. This course introduces the main principles, algorithms, and applications of machine learning, as well as important open source libraries and cloud-based machine learning services that practitioners are using to build real systems. Course Outcomes ● Students are able to implement and analyze ML algorithms ● Students are able to describe the formal properties of models and algorithms for ML and explain the practical implications of those results ● Students are able to select and apply the most appropriate ML method to solve a given learning problem Major Topics Covered in Course ● Overview of Machine Learning (ML) ● Logistic Regression, Softmax ● Neural Networks, Convolutional Neural Networks ● Decision Trees and Ensembles ● NLP ● Reinforcement Learning ● Unsupervised Learning