Networks, also known as graphs, are one of the most crucial data structures in our increasingly intertwined world. Social friendship networks, the web, financial systems, and infrastructure are all network structures. Knowing how to analyze the underlying network topology of interconnected systems can provide an invaluable skill in anyone’s toolbox.
Noemi Derzsy explains how to generate, manipulate, analyze, and visualize graph structures that will help you gain insight about relationships between elements in your data. You’ll start by exploring the basic network types and the most-often-encountered network models in real data. You’ll learn the most informative network measures to understand the network structure and behaviors. Noemi then walks you through using public social networks data to construct, analyze, and visualize the social network and understand the structure and connectivity behaviors. You’ll leave with the knowledge you need to take on a network analysis project.
Noemi Derzsy is a senior inventive scientist within the Data Science and AI Research organization at AT&T Labs. Previously, Noemi was a data science fellow at Insight Data Science NYC and a postdoctoral research associate at Social Cognitive Networks Academic Research Center at Rensselaer Polytechnic Institute. She holds a PhD in physics with over a decade of research experience in network science and computer science. Her interests revolve around the study of complex systems and complex networks through real-world data.
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