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

• Lecture Notes
• Assignment 3 Notes

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.