An Introduction to Network Analysis
Data Scientist - Incremental Group
Abstract: Network analysis is the statistical description of observations from a system modelled as a graph, with entities conceptualized as nodes and the relationship among them as edges. This approach provides a powerful tool to model relationships in many complex real-world systems, such as those found in communication, natural, transport, financial and social networks. The use of network statistics allows measurement of the relative importance of nodes and edges in networks and techniques such as community detection allow identification of functional units. Data scientist and other data analysis practitioners that are unfamiliar with network analysis would benefit from adding this technique to their tool set. The talk will provide an introduction to these technique and examples of typical applications in social and transportation networks, using open data and open source tools will be demonstrated.
Bio: Ricardo Antunes is a data scientist at Incremental Group where he runs many forms of data analysis, modelling and machine learning. Originally trained as a marine biologist, he used to split is time between chasing whales at sea and writing code for data analysis. After years of working in academia and non-profit sector, a passion for data analysis led to a role helping organizations to gain insight from data. When not writing code, Ricardo spends time sailing, building electronics and photographing wildlife.