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The course website: http://cs231n.stanford.edu/

You can see more details about experiments in my blog: http://danielcai0429.com/blog/wordpress/index.php/tag/cs231n

• 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) [done!]
  • Q2: Batch Normalization (30 points)[done!]
  • Q3: Dropout (10 points)[done!]
  • Q4: ConvNet on CIFAR-10 (30 points)[done!]
• Assignment #3
  • Q1: Image Captioning with Vanilla RNNs (40 points)[done!]
  • 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)