딥러닝 / CS231N / ASSIGNMENT
ASSIGNMENT
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Assignment 2-2: Dropout
Dropout 개념 및 구현
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Assignment 2-1: Batch Normalization
Batch Norm, Layer Norm
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Assignment 1-5: Training a fully connected network
FullyConnectedNet 구현, Momentum, RMSProp, Adam
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Assignment 1-4: Higher Level Representations: Image Features
HOG, HSV feature 추출과 feature 기반 분류기 학습
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Assignment 1-3: Two-Layer Neural Network
완전연결계층 구현
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Assignment 1-2: Implement a Softmax classifier
softmaxloss 구현, SGD 구현
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Assignment 1-1: k-Nearest Neighbor classifier
kNN 구현, training, testing, cross-validation