Using a multi-class Logistic Regression and a Neural Network with regularization to identify handwritten digits
Developed and written by Arnold Yeung
This project runs multi-class logistic regression and neural network with regularization for a dataset containing the pixels of handwritten digits. The dataset used is a subset of MNIST handwritten digits (http://yann.lecun.com/exdb/mnist).
This project is based on Exercises 3 and 4 in Coursera course, Machine Learning by Andrew Ng, Stanford University (https://www.coursera.org/learn/machine-learning).
All scripts and functions attached in this project, with the following exceptions, were written by Arnold Yeung:
The main pipeline script is run.m
For more information, please visit www.arnoldyeung.com
If you have any questions or comments, feel free to contact me at firstname.lastname@example.org