CS231n: Deep Learning for Computer Vision assignments - Spring 2025

This repository contains my solutions to the assignments of the CS231n course offered by Stanford University (Spring 2025).

Find course notes and assignments here and be sure to check out the video lectures for Spring 2017

any questions please email to newhaneul1234@gmail.com

My assignment solutions for CS231n

Assignment 1:

• Q1: K-Nearest Neighbor classifier (Done)
  
• Q2: Implement a Softmax classifier (Done)
  
• Q3: Two-Layer Neural Network (Done)
  
• Q4: Higher Level Representations: Image Features (Done)
  
• Q5: Training a fully connected network (Done)
  

Assignment 2:

• Q1: Batch Normalization (Done)
  
• Q2: Dropout (Done)
  
• Q3: Convolutional Neural Networks (Done)
  
• Q4: PyTorch on CIFAR-10 (Done)
  
• Q5: Image Captioning with Vanilla RNNs (Done)
  

Assignment 3:

• Q1: Image Captioning with Transformers (Done)
  
• Q2: Self-Supervised Learning for Image Classification (Done)
  
• [Q3]: Denoising Diffusion Probabilistic Models (yet)
  
• [Q4]: CLIP and Dino: Image Features (yet)