Deep Learning
Course description
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This course provides theories and applications of deep learning and AI. We cover diverse studies from fundamentals of deep learning (e.g., multi-layer perceptron, convolutional neural networks, backpropagation, supervised & un-/semi-/self-supervised learning, etc.) to recent learning-based computer vision applications (e.g., semantic & geometric tasks, image recognition, generative models, etc.). Recent advances in these studies will be dealt with in programming sessions using PyTorch, and regular paper review sessions organized by the enrolled students with presentations
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