Download EBOOK Understanding Machine Learning: From Theory to Algorithms PDF for free


Download EBOOK Understanding Machine Learning: From Theory to Algorithms PDF for free Category: Computing
The author of the book: Shai Shalev-Shwartz
Format files: PDF, EPUB, TXT, DOCX
The size of the: 131 KB
Language: English
ISBN-13: 9781107057135
Edition: CAMBRIDGE UNIVERSITY PRESS
Date of issue: 17 July 2014

Description of the book "Understanding Machine Learning: From Theory to Algorithms":

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 a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed 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 PDF gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.

Download EBOOK Understanding Machine Learning: From Theory to Algorithms PDF for free


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Shai Shalev-Shwartz

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Download EBOOK Understanding Machine Learning: From Theory to Algorithms PDF for free



Download EBOOK Understanding Machine Learning: From Theory to Algorithms for free

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