bookJan 1, 2015Closed access

Understanding Machine Learning: From Theory To Algorithms

Hebrew University of Jerusalem · University of Waterloo

Abstract

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…

Citation impact

3,088
total citations
FWCI
99.39
Percentile
100%
References
192
Citations per year

Authors

2

Topics & keywords

Keywords
  • Computer science
  • Artificial intelligence
  • Field (mathematics)
  • Machine learning
  • Computational learning theory
  • Stability (learning theory)
  • Algorithmic learning theory
  • Stochastic gradient descent
UN Sustainable Development Goals
  • Quality Education
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