Probabilistic Machine Learning: An Introduction
Probabilistic Machine Learning: An Introduction
English | 2022 | ISBN: 0262046822 | 854 Pages | PDF True | 87 MB
English | 2022 | ISBN: 0262046822 | 854 Pages | PDF True | 87 MB
This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.