Name: Understanding Machine Learning: From Theory to Algorithms (en Inglés)
Price: 279128.00 COP
Availability: InStock
Author: Shalev-Shwartz, Shai ; Ben-David, Shai
ISBN: 9781107057135

portada Understanding Machine Learning: From Theory to Algorithms (en Inglés)

Formato

Libro Físico

Autor

Shai Shalev-Shwartz

Shai Ben-David

Editorial

Cambridge University Press

Año

2014

Idioma

Inglés

N° páginas

409

Encuadernación

Tapa Dura

Dimensiones

25.7 x 17.5 x 2.8 cm

Peso

0.88 kg.

ISBN13

9781107057135

N° edición

Categorías

Reconocimiento de formas
Visión por ordenador

Understanding Machine Learning: From Theory to Algorithms (en Inglés)

Shai Shalev-Shwartz (Autor) · Shai Ben-David (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Understanding Machine Learning: From Theory to Algorithms (en Inglés)"

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.