DataHour: Introduction to Network Science

Network science is the study of patterns in interconnectedness of multiple entities. These entities can be from any domain. For example, friends from a network of friends in social media, employees from an employee network in an organization, financial securities in a network of financial assets and many more. Network science is applied in multiple domains to uncover internal structure of a complex system and also in many other applications like recommendation system, community detection, modeling spreading phenomenon etc.

In this DataHour, Bhaskarjit is going to cover a detailed introduction to network science and its different centrality measures. He’s also going to discuss various business use cases of network science.

Prerequisites:  Enthusiasm for learning Data Science.

Bhaskarjit Sarmah is a data scientist who builds predictive models for solving asset management business problems including trading, lending, risk management. His main research areas are Explainable AI, Uncertainty, Network Science, NLP and Computer VisionYou can follow him on Linkedin.