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A Light Introduction to Topological Data Analysis

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In this talk we will provide a high-level introduction to Topological Data Analysis, the use of computational methods to infer the topological features and geometric structures of complex datasets. Despite having origins dating back almost a century, the development of efficient algorithms in the last decade has led to explosion of renewed interest in the field. We will primarily focus on the motivation, intuition and practical concerns of such methods, and share applications in a range of fields, including neuroscience and computational chemistry.

This talk is part of the Machine Learning Reading Group @ CUED series.

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