Peters Jonas, Janzing Dominik, Schölkopf Bernhard. Elements of Causal Inference: Foundations and Learning Algorithms

Cambridge University Press, 2012. Корр. от 25 фев. 2014. — 672 p. — ISBN: 978-0521518147. Online-версия книги, периодически исправляемая и дополняемая автором. Книга имеет электронное оглавление и содержит цветные иллюстрации. Замеченные опечатки (errata) отмечены в тексте сиреневым (magenta) цветом, добавления (addenda) к бумажному изданию — синим (blue) цветом. Machine...

Cambridge: Cambridge University Press, 2020. — 398 p. — ISBN: 110845514X. Machine learning is the latest in a long line of attempts to distill human knowledge and reasoning into a form that is suitable for constructing machines and engineering automated systems. As machine learning becomes more ubiquitous and its software packages become easier to use, it is natural and...

3rd ed. — CRC Press, 2013. — 675 p. — ISBN: 1439840954. Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The...

2009. Massachusetts Institute of Technology. Не скан. Электронная версия книги. Motivation Structured Probabilistic Models Overview and Roadmap Historical Notes Foundations Probability Theory Graphs Relevant Literature Exercises The Bayesian Network Representation Exploiting Independence Properties Bayesian Networks Independencies in Graphs From Distributions to Graphs Relevant...

Massachusetts Institute of Technology, 2012. — 1067 p. — ISBN: 0262018020, 978-0262018029. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive...