How to reveal, characterize, and exploit the structure in data? Meeting this central challenge of modern data science requires the development of new mathematical approaches to data analysis, going beyond traditional statistical methods. Fruitful mathematical methods can originate in geometry, top
Topological Data Analysis with Applications
β Scribed by Gunnar Carlsson, Mikael Vejdemo-Johansson
- Publisher
- Cambridge University Press
- Year
- 2022
- Tongue
- English
- Leaves
- 233
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The continued and dramatic rise in the size of data sets has meant that new methods are required to model and analyze them. This timely account introduces topological data analysis (TDA), a method for modeling data by geometric objects, namely graphs and their higher-dimensional versions: simplicial complexes. The authors outline the necessary background material on topology and data philosophy for newcomers, while more complex concepts are highlighted for advanced learners. The book covers all the main TDA techniques, including persistent homology, cohomology, and Mapper. The final section focuses on the diverse applications of TDA, examining a number of case studies drawn from monitoring the progression of infectious diseases to the study of motion capture data. Mathematicians moving into data science, as well as data scientists or computer scientists seeking to understand this new area, will appreciate this self-contained resource which explains the underlying technology and how it can be used.
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<p><span>This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processingΒ and their applications in real world. The topics covered in machine learning involves featu
<p>Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the repre