Produs

Understanding Machine Learning: From Theory to Algorithms, Hardcover/Shai Shalev-Shwartz

Name: Understanding Machine Learning: From Theory to Algorithms, Hardcover/Shai Shalev-Shwartz
Brand: Cambridge University Press
Price: 382.99 RON
Availability: InStock

Vânzător

elefant.ro

Cumpără

Pret

382.99 Lei

Categorie (vânzător)

Foreign Books

Marca

Cambridge University Press

Produs actualizat în urmă cu 20 ore

Descriere YEO:

Understanding Machine Learning: From Theory - Disponibil la elefant.ro

Pe YEO găsești Understanding Machine Learning: From Theory de la Cambridge University Press, în categoria Foreign Books.

Indiferent de nevoile tale, Understanding Machine Learning: From Theory to Algorithms, Hardcover/Shai Shalev-Shwartz din categoria Foreign Books îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.

Preț: 382.99 Lei

Caracteristicile produsului Understanding Machine Learning: From Theory

Brand: Cambridge University Press
Categoria: Foreign Books
Magazin: elefant.ro
Ultima actualizare: 07-06-2026 00:30:09

Comandă Understanding Machine Learning: From Theory Online, Simplu și Rapid

Prin intermediul platformei YEO, poți comanda Understanding Machine Learning: From Theory de la elefant.ro rapid și în siguranță. Bucură-te de o experiență de cumpărături online optimizată și descoperă cele mai bune oferte actualizate constant.

Descriere magazin:
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.

Understanding Machine Learning: From Theory to Algorithms, Hardcover/Shai Shalev-Shwartz - 0 | YEO