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This introduction to topological data analysis keeps prerequisites to a minimum while covering all the key techniques, including persistent homology, cohomology, and Mapper. The final section discusses diverse case studies in detail. Mathematicians, data scientists and computer scientists will appreciate this graduate-level resource.

Produktbeschreibung
This introduction to topological data analysis keeps prerequisites to a minimum while covering all the key techniques, including persistent homology, cohomology, and Mapper. The final section discusses diverse case studies in detail. Mathematicians, data scientists and computer scientists will appreciate this graduate-level resource.
Autorenporträt
Gunnar Carlsson is Professor Emeritus at Stanford University. He received his doctoral degree from Stanford in 1976, and has taught at the University of Chicago, University of California, San Diego, Princeton University, and since 1991 at Stanford University. His work within mathematics has been concentrated in algebraic topology, and he has spent the last 20 years on the development of topological data analysis. He is also passionate about the transfer of scientific findings to real-world applications, leading him to the founding of the topological data analysis-based company Ayasdi in 2008.