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CS231n_Spring_2018_Assignment

CS231n: Convolutional Neural Networks for Visual Recognition, a course from stanford.

This is my CS231n course assignment repository, which includes 3 assignments and my handwritten notebooks. I worked through the assignments to reinforce my understanding of deep learning computer vision.

Notebooks

Assignment 1:

  • 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.

Assignment 2:

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

Assignment 3: (Done with TensorFlow)

  • 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.