Prerequisites: A strong mathematical background in calculus, linear algebra, and prob ability & statistics, as well as prior coursework in machine learning and programming experience in Python. Mathematical and machine learning background for deep learning. Feed-forward networks. Backpropagation. Training strategies for deep networks. Convolutional networks. Recurrent neural networks. Transformers. Diffusion Models. Deep unsupervised learning. Exposure to Pytorch and other modern programming tools. Other recent topics, time permitting. Same as CAS CS 523. Students may not receive credit for both.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.