Machine Learning: A First Course for Engineers and Scientists

ISBN-13: 9781108843607 / Angielski / Twarda / 2022 / 325 str.

Sweden) Schoen Thomas B. (Uppsala Universitet

Opis

Presents carefully selected supervised and unsupervised learning methods from basic to state-of-the-art,in a coherent statistical framework.

Recenzje

'This book strikes a very good balance between accessibility and rigour. It will be a very good companion for the mathematically trained who want to understand the hows and whats of machine learning.' Ole Winther, University of Copenhagen and Technical University of Denmark

Spis treści

1. Introduction; 2. Supervised learning: a first approach; 3. Basic parametric models and a statistical perspective on learning; 4. Understanding, evaluating and improving the performance; 5. Learning parametric models; 6. Neural networks and deep learning; 7. Ensemble methods: Bagging and boosting; 8. Nonlinear input transformations and kernels; 9. The Bayesian approach and Gaussian processes; 10. Generative models and learning from unlabeled data; 11. User aspects of machine learning; 12. Ethics in machine learning.