Homeworks for CS5145701 Deep Learning for Computer Vision Applications (Spring 2018)

In the spring of 2018, I was a Teaching Assistant for the graduate class on "Deep Learning for Computer Vision Applications (CS5145701)" at National Taiwan University of Science and Technology. I was in-charge of making all the slides for the class and also the assignments given to the students.

This repository contains the released assignments in the form of jupyter notebooks which guides the students in implementing basic machine learning algorithms that forms the foundations of neural networks / deep learning.

All code is written in Python 3 and uses numpy as its core library for implementing the algorithms. Please let me know if you find any errors / bugs.

Table of Contents

• k-Nearest Neighbors (Adopted from Stanford's CS231n class)
• Linear Regression
• Polynomial Regression and Regularized Regression
• Logistic Regression
• Multinomial Logistic Regression (SoftMax)
• Neural Networks (WIP)