please visit course website http://cs231n.stanford.edu/ for more information about the course
and visit http://cs231n.github.io/ for assignment information
Assignment list:
- 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!]
- Assignment #2
- Q1: Fully-connected Neural Network (30 points) [*** working ***]
- Q2: Batch Normalization (30 points)
- Q3: Dropout (10 points)
- Q4: ConvNet on CIFAR-10 (30 points)
- Assignment #3
- Q1: Image Captioning with Vanilla RNNs (40 points)
- Q2: Image Captioning with LSTMs (35 points)
- Q3: Image Gradients: Saliency maps and Fooling Images (10 points)
- Q4: Image Generation: Classes, Inversion, DeepDream (15 points)