My homeworks for Stanford CS231n (Spring 2017)
Assignment 1:
| Question | Status |
|---|---|
| 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 |
Assignment 2:
| Question | Status |
|---|---|
| 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 (TF) |
Assignment 3:
| Question | Status |
|---|---|
| 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 (TF) |
| Q4: Style Transfer (15 points) | Done (TF) |
| Q5: Generative Adversarial Networks (15 points) | Done (TF) |