This repo stores the code for the assignments in the course CS231n: Convolutional Neural Networks for Image Recognition taught at Stanford and is consistent with the 2018 version of the course. Further details can be found here: cs231n.github.io

The following questions have been completed:

Assignment 1:

• Q1: k-Nearest Neighbor Classifier (Done)
• Q2: Training a Support Vector Machine (Done)
• Q3: Implement a Softmax classifier (Done)
• Q4: Two-Layer Neural Network (Done)

Assignment 2:

• Q1: Fully Connected Neural Network (Done)
• Q2: Batch Normalization (Done)
• Q3: Dropout (Done)
• Q4: Convolutional Networks (Done)
• Q5: PyTorch/Tensorflow on CIFAR-10 (Done in PyTorch)

Assignment 3:

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

Important
The code particularly in the jupyter notebooks is written such that it would work on Google Colab since I didn't have enough compute on my local machine.