Networks, also know as graphs, are one of the most crucial data structures in our increasingly intertwined world. Social friendship networks, the world-wide web, financial systems, infrastructure (power grid, streets), etc. are all network structures. Knowing how to analyze the underlying network topology of interconnected systems can provide an invaluable skill in anyone's toolbox. This tutorial will provide a hands-on guide on how to approach a network analysis project from scratch and end-to-end: how to generate, manipulate, analyze and visualize graph structures that will help you gain insight about relationships between elements in your data.


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Tutorial Overview

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    ODSC West 2020: Exploring the Interconnected World: Network/Graph Analysis in Python

    • Tutorial Overview and Author Bio

    • Before you get started: Prerequisites and Resources

    • Tutorial Slides

    • Exploring the Interconnected World: Network/Graph Analysis in Python

Instructor Bio:

Noemi Derzsy

Senior Inventive Scientist | AT&T Chief Data Office

Noemi Derzsy, PhD

Noemi Derzsy is a Senior Inventive Scientist at AT&T Chief Data Office within the Data Science and AI Research organization. Her research is centered on understanding and modeling customer behavior and experience through large-scale consumer and network data, using machine learning, network analysis/modeling, spatio-temporal mining, text mining and natural language processing techniques. Prior to joining AT&T, 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, MS in Computational Physics, and has a research background in Network Science and Computer Science. Noemi is also involved in volunteering in the data science community. She is a NASA Datanaut and former organizer of the Data Umbrella meetup group and NYC Women in Machine Learning and Data Science meetup group.