https://github.com/sbyeol3/cs231n-study

CS231n Lecture Assignment Codes 📊
https://github.com/sbyeol3/cs231n-study

computer-vision jupyter-notebook python3

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CS231n Lecture Assignment Codes 📊

• Host: GitHub
• URL: https://github.com/sbyeol3/cs231n-study
• Owner: sbyeol3
• Created: 2020-01-13T10:45:42.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T05:25:43.000Z (almost 2 years ago)
• Last Synced: 2023-03-04T13:18:05.116Z (over 1 year ago)
• Topics: computer-vision, jupyter-notebook, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 1.39 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 15
• Metadata Files:
  • Readme: README.md

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README

        
# CS231n Assignment :fire:

- :books: 이화여대 블록체인학회 EWHA-CHAIN 내 인공지능 스터디 (2020.01-2020.02) 

- :running: 스터디원 : 성원, 샛별, 지희, 효진

- :dizzy: CS231n 완강 및 Assignment 풀기

> ref : [CS231n github.io Link](http://cs231n.github.io/assignments2019/assignment1/) 

## Assignment 1

- :ballot_box_with_check: Q1 : k-Nearest Neighbor classifier

- :ballot_box_with_check: Q2 : Training a Support Vector Machine

- :ballot_box_with_check: Q3 : Implement a Softmax classifier

- Q4 : two-layer NN

- Q5 : higher level representation # Image Features

## Assignment 2

- Q1 : Fully-connected Neural Network

  - [참고](https://kratzert.github.io/2016/02/12/understanding-the-gradient-flow-through-the-batch-normalization-layer.html)

- Q2 : Batch Normalization

- Q3 : Dropout

- Q4 : Convolutional Networks 

- Q5 : PyTorch / TensorFlow on CIFAR-10 

## 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