Machine Learning With Graphs

This repository includes two jupyter notebooks I have made while learning to use the package NetworkX and applying machine learning to a Graph.

1. I learnt networkx via https://www.youtube.com/watch?v=Q7aVQ5FtEBU&list=PL2VXyKi-KpYsjoY2rx9NiWJyfmmD79H97 , a Python for Social Networks, produced by Dr. William Mattingly. The exercises are stored in learning_networkx.ipynb

2. I attempt to apply machine learning to a graph. The codes are stored in link_prediction.ipynb.

The dataset is based on Facebook pages wherein :

• G = (V,E)
• V = Facebook pages of chefs and restaurants.
• E = If they have liked each other.

DISCLAIMER : It is a directed graph, because a chef page can like a restaurant page but the restaurant page may not like the chef page back and vice versa. However, for the sake of application towards another assignment, I will assume it is an undirected graph.