cs231n

CS231N Stanford University programming assignments

Installation

conda create -n cs231n python=3 anaconda
conda activate cs231n

Assignment 1

cd assignment1
./install_packages.sh
cd cs231n/datasets
./get_datasets.sh

• Q1: k-Nearest Neighbor classifier, knn.ipynb
• Q2: Training a Support Vector Machine, svm.ipynb
• Q3: Implement a Softmax classifier, softmax.ipynb
• Q4: Two-Layer Neural Network, two_layer_net.ipynb
• Q5: Higher Level Representations: Image Features, features.ipynb

Assignment 2

cd assignment2
./install_packages.sh
cd cs231n/datasets
./get_datasets.sh

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

Assignment 3

• Q1: Image Captioning with Vanilla RNNs, RNN_Captioning.ipynb
• Q2: Image Captioning with LSTMs
• Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images, NetworkVisualization-PyTorch.ipynb
• Q4: Style Transfer, StyleTransfer-PyTorch.ipynb
• Q5: Generative Adversarial Networks, Generative_Adversarial_Networks_PyTorch.ipynb