Understanding Machine Learning
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 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 gradient descent,…
Citation impact
- FWCI
- 13.85
- Percentile
- 100%
- References
- 0
Authors
2Topics & keywords
- Computer science
- Artificial intelligence
- Stability (learning theory)
- Algorithmic learning theory
- Computational learning theory
- Machine learning
- Presentation (obstetrics)
- Stochastic gradient descent
- Quality Education