The course website: http://cs231n.stanford.edu/
My own solutions for CS231N -2018
Assignment list:
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Assignment #1
- Q1: k-Nearest Neighbor classifier (20 points) [-done-]
- Q2: Training a Support Vector Machine (25 points) [-done-]
- Q3: Implement a Softmax classifier (20 points) [-done-]
- Q4: Two-Layer Neural Network (25 points) [-done-]
- Q5: Higher Level Representations: Image Features (10 points) [-done-]
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Assignment #2
- Q1: Fully-connected Neural Network (25 points) [-done-]
- Q2: Batch Normalization (25 points) [-done-]
- Q3: Dropout (10 points) [-done-]
- Q4: Convolutional Networks (30 points) [-done-]
- Q5: PyTorch / Tensorflow on CIFAR-10 (10 points)[-done-]
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Assignment #3
- Q1: Image Captioning with Vanilla RNNs (25 points)[-done-]
- Q2: Image Captioning with LSTMs (30 points)[-done-]
- Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images (15 points) [-done-]
- Q4: Style Transfer (15 points)[-done-]
- Q5: Generative Adversarial Networks (15 points)[-done-]