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Автор: Yi Sun, Rod Adams
Издательство: Springer
Год: 2025
Страниц: 486
Язык: английский
Формат: pdf (true), epub
Размер: 39.9 MB
This textbook provides a comprehensive foundation in the mathematics needed for Data Science for students and self-learners with a basic mathematical background who are interested in the principles behind computational algorithms in Data Science. It covers sets, functions, linear algebra, and calculus, and delves deeply into probability and statistics, which are key areas for understanding the algorithms driving modern Data Science applications. Readers are guided toward unlocking the secrets of algorithms like Principal Component Analysis, Singular Value Decomposition, Linear Regression in two and more dimensions, Simple Neural Networks, Maximum Likelihood Estimation, Logistic Regression and Ridge Regression, illuminating the path from mathematical principles to algorithmic mastery. It is designed to make the material accessible and engaging, guiding readers through a step-by-step progression from basic mathematical concepts to complex Data Science algorithms. This approach facilitates a smoother transition into more advanced topics. Examples in Python.