The Calabi–Yau Landscape From Geometry, to Physics, to Machine Learning

“The description of the geometry of Calabi–Yau manifolds at the beginning of the book is directed to readers with a solid geometric background … . The book mainly consists of a clear presentation on how neutral networks and machine learning tools can be usefully employed to interact (with a statistically high rate of success) with deep theoretical studies of geometric objects.” (Luca Chiantini, zbMATH 1492.14001, 2022)

“The book assists the reader in such outsourced learning. It is structured as a sort of hypertext that provides general context and a big picture with embedded ‘links’ (references) to the more specialized literature. … The message of the Calabi-Yau landscape is that it is time for both to learn data science, and this book is a fine place to start.” (Sergiy Koshkin, Mathematical Reviews, October, 2022)