cs231n

My solutions for this course (Spring 2017).

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

• assignment1

  • Q1: k-Nearest Neighbor classifier ✅
  • Q2: Training a Support Vector Machine ✅
  • Q3: Implement a Softmax classifier ✅
  • Q4: Two-Layer Neural Network ✅
  • Q5: Higher Level Representations: Image Features ✅

• assignment2

  • Q1: Fully-connected Neural Network ✅
  • Q2: Batch Normalization ✅
  • Q3: Dropout ✅
  • Q4: Convolutional Networks ✅
  • Q5: PyTorch / TensorFlow on CIFAR-10 ✅

• assignment3

  • 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 ✅

Screenshots

Style Transfer

Class Visualization

Generative Adversarial Networks