딥러닝개론(공)

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SE395 딥러닝개론(공)
과목번호 SE395
학점/이론시수/실습시수 3.0/3.0/0.0
교과구분
이학/공학
대분류
소분류
최초개설연도
교수자
개설학년
개설학기
교재

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선수과목

개요

This course provides the introductory materials for deep learning, which is a machine learning methodology that learns multiple layers of non-linear representations. This course will also cover some of its applications to computer vision and natural language processing.

주차별계획

1주차:Introduction 2주차:Machine learning review 3주차:Multilayer perceptron 4주차:Regularization for deep learning 5주차:Optimization for deep learning 6주차:Convolutional neural networks 7주차:Convolutional neural networks 8주차:Midterm 9주차:Deep learning framework 10주차:Recurrent neural networks 11주차:Auto-encoders 12주차:Generative adversarial networks 13주차:Generative adversarial networks 14주차:Reinforcement learning 15주차:Deep Learning Limitation & Research Issues 16주차:Final exam

평가방법

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