- π μ΄νμ¬λ λΈλ‘체μΈνν EWHA-CHAIN λ΄ μΈκ³΅μ§λ₯ μ€ν°λ (2020.01-2020.02)
- π μ€ν°λμ : μ±μ, μλ³, μ§ν¬, ν¨μ§
- π« CS231n μκ° λ° Assignment νκΈ°
ref : CS231n github.io Link
- βοΈ Q1 : k-Nearest Neighbor classifier
- βοΈ Q2 : Training a Support Vector Machine
- βοΈ Q3 : Implement a Softmax classifier
- Q4 : two-layer NN
- Q5 : higher level representation # Image Features
- Q1 : Fully-connected Neural Network
- Q2 : Batch Normalization
- Q3 : Dropout
- Q4 : Convolutional Networks
- Q5 : PyTorch / TensorFlow on CIFAR-10
- Q1 : Image Captioning with Vanilla RNNs
- Q2 : Image Captioning with LSTMs
- Q3 : Network Visualization # Saliency maps, Class Visualization, and Fooling Images
- Q4 : Style Transfer
- Q5 : Generative Adversarial Networks