CmpE 597 Deep Learning

Catalog Description: 

Convolutional neural networks. Autoencoders, their sparse, denoising variants, and their training. Regularization methods for preventing overfitting. Stacked autoencoders and end-to-end networks. Recurrent and recursive networks. Multimodal approaches. Deep architectures for vision, speech, natural language processing, and reinforcement learning.


(3+0+0) 3 ECTS 6


Consent of the instructor
Offering Course Page Instructor
CmpE 597 Deep Learning 2018 Spring Ethem Alpaydın
CmpE 597 Deep Learning 2017 Spring Ethem Alpaydın

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Department of Computer Engineering, Boğaziçi University,
34342 Bebek, Istanbul, Turkey

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