Глубокое понимание машинного обучения: от принципа к первоначальному изучению обучения Шалев-Шварц, Шай Бен-Дэвид [Китайское издание Шан]]
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Описание товара
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Understanding Machine Learning
Shai Shalev-Shwartz (Author), Shai Ben-David (Author)
Hardcover: 410 pages
Publisher: Cambridge University Press (May 19 2014)
Language: English
ISBN-10: 1107057132
ISBN-13: 978-1107057135
Product Dimensions: 18.3 x 2.8 x 26 cm
Shipping Weight: 907 g
Параметры страницы предназначены только для справки, а специфика основана на реальном объекте
краткое введение
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way.
The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks.
These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering.