Studies

192
Compulsory

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Topological data analysis is a new area which seeks to apply methods from topology to study the "shape" of data sets. It is particularly suited to noisy data sets sitting in potentially high (e.g., 10,000) dimensional spaces, which are none-the-less concentrated around low-dimensional geometric structures that need to be uncovered.

Despite being a new area, topological data analysis has already seen applications in several areas of science and engineering, including oncology, astronomy, neuroscience, image processing, and biophysics.

For more information see:
http://www.mi.fu-berlin.de/users/shanekelly/TopologicalDataAnalysis2017SS.html

Topological data analysis is a new area which seeks to apply methods from topology to study the "shape" of data sets. It is particularly suited to noisy data sets sitting in potentially high (e.g., 10,000) dimensional spaces, which are none-the-less concentrated around low-dimensional geometric structures that need to be uncovered.

Despite being a new area, topological data analysis has already seen applications in several areas of science and engineering, including oncology, astronomy, neuroscience, image processing, and biophysics.

For more information see: http://www.mi.fu-berlin.de/users/shanekelly/TopologicalDataAnalysis2017SS.html

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