Understanding Machine Learning

Understanding Machine Learning: From Theory to Algorithms, 1st Edition, introduces the fundamentals of machine learning and its algorithmic paradigms in a principled manner.

The textbook presents a theoretical account of the principles underlying machine learning, using mathematical derivations to connect core concepts to practical algorithms. Coverage includes foundational theory alongside algorithmic paradigms such as stochastic gradient descent.

Designed for advanced undergraduates and beginning graduate students, the volume provides accessible instruction for readers across computer science, statistics, mathematics, and engineering.