adityakuppa26 / CS231N-Assignment-Solutions

Solutions for Stanford's CS231N: Convolutional Neural Networks for Visual Recognition Course Assignment Solutions

CS231n: Convolutional Neural Networks for Visual Recognition Assignment Solutions

This repository contains my solutions to the assignments of the CS231n course offered by Stanford University.

Assignment 1:

Q1: k-Nearest Neighbor classifier. (Completed)
Q2: Training a Support Vector Machine. (Completed)
Q3: Implement a Softmax classifier. (Completed)
Q4: Two-Layer Neural Network. (Completed)
Q5: Higher Level Representations: Image Features. (Completed)

Assignment 2:

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

Assignment 3:

Q1: Image Captioning with RNNs. (Completed)
Q2: Image Captioning with LSTMs. (Completed)
Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images. (Completed in PyTorch)
Q4: Style Transfer. (Completed in PyTorch)