Description
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.
Author: Alexander Jung
Publisher: Springer
Published: 01/22/2022
Pages: 212
Binding Type: Hardcover
Weight: 1.11lbs
Size: 9.21h x 6.14w x 0.56d
ISBN13: 9789811681929
ISBN10: 9811681929
BISAC Categories:
- Computers | Artificial Intelligence | General
- Computers | Information Theory
- Computers | Computer Science
Author: Alexander Jung
Publisher: Springer
Published: 01/22/2022
Pages: 212
Binding Type: Hardcover
Weight: 1.11lbs
Size: 9.21h x 6.14w x 0.56d
ISBN13: 9789811681929
ISBN10: 9811681929
BISAC Categories:
- Computers | Artificial Intelligence | General
- Computers | Information Theory
- Computers | Computer Science
About the Author
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.
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