Advanced Machine Learning and Neural Networks

Advanced Machine Learning and Neural Networks

MET CS 767 (4 credits)

Graduate Prerequisites: MET CS 521; MET CS 622, MET CS 673 or MET CS 682; MET CS 677 strongly recommended; or consent of instructor. - Theories and methods for learning from data. The course covers a variety of approaches, including Supervised and Unsupervised Learning, Regression, k-means, KNN’s, Neural Nets and Deep Learning, Recurrent Neural Nets, Rule-learning, Adversarial Learning, Bayesian Learning, and Genetic Algorithms. The underpinnings are covered: perceptrons, backpropagation, attention, and transformers. Each student focuses on two of these approaches and creates a term project.

2024FALLMETCS767A1, Sep 3rd to Dec 10th 2024

2024FALLMETCS767A2, Sep 3rd to Dec 10th 2024

2024FALLMETCS767O2, Oct 29th to Dec 16th 2024