Understanding Machine Learning: From Theory to Algorithms

Understanding Machine Learning: From Theory to Algorithms

Shai Shalev-Shwartz


computing device studying is likely one of the quickest turning out to be components of laptop technology, with far-reaching functions. the purpose of this textbook is to introduce laptop studying, and the algorithmic paradigms it bargains, in a principled method. The publication presents an intensive theoretical account of the basic principles underlying laptop studying and the mathematical derivations that remodel those ideas into useful algorithms. Following a presentation of the fundamentals of the sector, the booklet covers a big selection of critical issues that experience no longer been addressed through earlier textbooks. those comprise a dialogue of the computational complexity of studying and the innovations of convexity and balance; very important algorithmic paradigms together with stochastic gradient descent, neural networks, and established output studying; and rising theoretical strategies corresponding to the PAC-Bayes procedure and compression-based bounds. Designed for a complicated undergraduate or starting graduate path, the textual content makes the basics and algorithms of computer studying available to scholars and non-expert readers in records, desktop technological know-how, arithmetic, and engineering.

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