Graphs for Data Science

• Real-world datasets to show how graphs really work
• Intuitive explanations of algorithms
• Practical application of algorithms to large datasets

Graphs are deceptively simple concepts: a set of individual Nodes (components) connected by Edges (relationships). In this very simplicity lies their power. They can describe the structure of our friendships, connections between airports, the spread of diseases from person to person, the relation of one concept to another, how species interact in an ecosystem, or how computers communicate to form the World Wide Web.

Networks are the fundamental language of our increasingly complex world and the key to successfully understanding it. By exploring in detail the way graphs can be used to explore, describe, analyze, and understand empirical datasets, we will put you at the forefront of this growing field.

In this tutorial, we will use Python's NetworkX to build our understanding of network representations and algorithms by exploring real-world network datasets such as the BTS airline transportation network, the BitCoin transaction network, the road network of OpenStreetMap, etc. Through this practical approach, attendees will better understand the fundamental ideas and concepts that lie at the base of our increasingly complex world and take the first steps toward being at the forefront of this growing field.