Top 8 Graph Algorithms every Data Scientist Should Know

Consolidated list of Definitions, visuals, key characteristics, real-time applications.

Photo by Isaac Smith on Unsplash

If you are planning to give your next data science interview, this article may help you out with some frequently asked data structure algorithms during the interview. Here is the list of my favorite graph algorithms which have great applications as well.

The compilation of all the important graph algorithms is generally asked in data science interview questions.

1. Breadth-First Search: BFS is a method of exploring a tree or graph. In this algorithm, you first explore the nodes which are just one step away, then the nodes which are two-step away, and so on. As the name suggests, you first explore the nodes breadthwise then go into depth.

Key characteristics: BFS is used for finding the shortest path in an undirected graph.

Real-time applications of BFS algorithm:

1. BFS is used in GPS navigation systems to find neighboring places.
2. BFS can also be used in networking for broadcasting a few packets.
3. It is used as a crawler in search engines to display all the resulting links related to the source search.