Machine Learning

Alexander Jung is Assistant Professor of Machine Learning at the Department of Computer Science, Aalto University where he leads the research group "Machine Learning for Big Data". His courses on machine learning, artificial intelligence, and convex optimization are among the most popular courses offered at Aalto University. He received a Best Student Paper Award at the premium signal processing conference IEEE ICASSP in 2011, an Amazon Web Services Machine Learning Award in 2018, and was elected as Teacher of the Year by the Department of Computer Science in 2018. He serves as an Associate Editor for the IEEE Signal Processing Letters.

“The book under review matured from lecture notes … . The structure and style strongly recommend the book as a thorough entry point for studying ML; the exercises and the references concluding each chapter reinforce concepts and also provide a curated guidance for further steps. … The (text)book reaches a balance between mathematical details, overview of algorithms and examples, making it suitable for a wide range of readers, and further underlining the interdisciplinary character of machine learning.” (Irina Ioana Mohorianu, zbMATH 1530.68002, 2024)

• Introduction.- Components of ML.- The Landscape of ML.- Empirical Risk Minimization.- Gradient-Based Learning.- Model Validation and Selection.- Regularization.- Clustering.- Feature Learning.- Transparant and Explainable ML.