CS231n

Spring 2018 assignments and some notes from the Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition

Spring 2018 Assignments

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: TensorFlow & PyTorch on CIFAR-10

Assignment 3

• Q1: Image Captioning with Vanilla RNNs
• Q2: Image Captioning with LSTMs
• Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images (TensorFlow & PyTorch)
• Q4: Style Transfer (TensorFlow & PyTorch)
• Q5: Generative Adversarial Networks (TensorFlow & PyTorch)