CS231n: Convolutional Neural Networks for Visual Recognition

Stanford / Spring 2019

This repository is my implementation of assignments and projects for the 2019 version of CS231n: Convolutional Neural Networks for Visual Recognition by Stanford University.

• Course Page: http://cs231n.stanford.edu/
• Github Page: https://cs231n.github.io/
• Lecture Videos: YouTube (2017)

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 on CIFAR-10

Version: PyTorch 1.4.0

Assignment 3

✅ 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

Version: PyTorch 1.4.0