It takes the average reader 4 hours and 55 minutes to read Mathematical Principles of Topological and Geometric Data Analysis by Parvaneh Joharinad
Assuming a reading speed of 250 words per minute. Learn more
This book explores and demonstrates how geometric tools can be used in data analysis. Beginning with a systematic exposition of the mathematical prerequisites, covering topics ranging from category theory to algebraic topology, Riemannian geometry, operator theory and network analysis, it goes on to describe and analyze some of the most important machine learning techniques for dimension reduction, including the different types of manifold learning and kernel methods. It also develops a new notion of curvature of generalized metric spaces, based on the notion of hyperconvexity, which can be used for the topological representation of geometric information. In recent years there has been a fascinating development: concepts and methods originally created in the context of research in pure mathematics, and in particular in geometry, have become powerful tools in machine learning for the analysis of data. The underlying reason for this is that data are typically equipped with some kind of notion of distance, quantifying the differences between data points. Of course, to be successfully applied, the geometric tools usually need to be redefined, generalized, or extended appropriately. Primarily aimed at mathematicians seeking an overview of the geometric concepts and methods that are useful for data analysis, the book will also be of interest to researchers in machine learning and data analysis who want to see a systematic mathematical foundation of the methods that they use.
Mathematical Principles of Topological and Geometric Data Analysis by Parvaneh Joharinad is 287 pages long, and a total of 73,759 words.
This makes it 97% the length of the average book. It also has 90% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 6 hours and 43 minutes to read Mathematical Principles of Topological and Geometric Data Analysis aloud.
Mathematical Principles of Topological and Geometric Data Analysis is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
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