Название: Mathematical Pictures at a Data Science Exhibition Автор: Simon Foucart Издательство: Cambridge University Press Год: 2022 Страниц: 339 Размер: 10,17 МБ Формат: PDF Язык: English
This text provides deep and comprehensive coverage of the mathematical background for data science, including machine learning, optimal recovery, compressed sensing, optimization, and neural networks. In the past few decades, heuristic methods adopted by big tech companies have complemented existing scientific disciplines to form the new field of Data Science. This text embarks the readers on an engaging itinerary through the theory supporting the field. Altogether, twenty-seven lecture-length chapters with exercises provide all the details necessary for a solid understanding of key topics in data science. While the book covers standard material on machine learning and optimization, it also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressed sensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background will appreciate the appendices that provide more background on some of the more abstract concepts.
Уважаемый посетитель, Вы зашли на сайт как незарегистрированный пользователь.
С этой публикацией часто скачивают:
Data Science for Nano Image Analysis Название: Data Science for Nano Image Analysis Автор: Chiwoo Park, Yu Ding Издательство: Springer Год: 2021 Страниц: 376 Язык: английский Формат: pdf...
Information-Theoretic Methods in Data Science Название: Information-Theoretic Methods in Data Science Автор: Miguel R. D. Rodrigues, Yonina C. Eldar Издательство: Cambridge University Press Год:...
Навигация
Вход на сайт
Реклама
Mathematical Pictures at a Data Science Exhibition 
