Hi,
This repository contains my work for the third project of the GE-461: Introduction to Data Science course.
In this project, we are looking at basic supervised learning by implementing an Artificial Neural Network. For our case, we will consider two types of ANNs: one with a single output neuron (a simple linear regressor) and the other with a single hidden layer. We will explore how the different configurations perform on the 1-dimensional dataset given. My report can be accessed here: https://xmassmx.github.io/GE-461-Supervised-Learning/
Note: Please do not copy this work and stay away from plagiarism. The work in this repository is my solution and is meant to be used as a guide only.