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Top Data Analysis
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Top Data Analysis
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Academic year 2019/2020
- Teaching staff
- Ulderico Fugacci
Francesco Vaccarino - Type
- Basic
- Credits/Recognition
- 4
- Course disciplinary sector (SSD)
- MAT/03 - geometria
- Delivery
- Formal authority
- Language
- English
- Attendance
- Obligatory
- Type of examination
- Oral
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Sommario del corso
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Course objectives
Introducing at TDA with a strong focus on persistent homology.
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Results of learning outcomes
Finding persistent topological holes, voids and emptinesses.
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Program
The aim of this course is to introduce graduate student to Topological Data Analysis (TDA), which is a novel framework of techniques, mainly devoted to producing summaries of complex data sets. Based on algebraic topology, TDA has several applications and presents many open research problems. The course will start with a crash introduction to homology, followed by a thorough insight on persistent homology. Applications to real data and computational issues as well as an account of the existing software will be presented as well.
Suggested readings and bibliography
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