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CISC 473 Deep Learning Units: 3.00
Design of deep neural networks based on leading-edge algorithms such as Restricted Boltzmann Machines, Recurrent Neural Networks, Convolutional Neural Networks, Long-Short Term Machines. Autoencoding as a clustering technique. Applications to prediction problems in natural language and images.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 371 or [CISC 271 and CISC 352]).
Offering Faculty: Faculty of Arts and Science