Probabilistic Machine Learning by Kevin P. Murphy (Author)

Dimensions:

176 mm × 250 mm

17.6 cm × 25 cm

6.93 inches × 9.84 inches

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.