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llqvofptfiztvjwc – Read and download Jonas Peters’s book Elements of Causal Inference : Foundations and Learning Algorithms in PDF, EPub, Mobi, Kindle online. Book Elements of Causal Inference : Foundations and Learning Algorithms by Jonas Peters

Elements of Causal Inference : Foundations and Learning Algorithms
by Jonas Peters

Summary: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts. show more

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Product details Format Hardback | 288 pages Dimensions 178 x 229 x 22mm | 680.39g Publication date 29 Nov 2017 Publisher MIT Press Ltd Imprint MIT Press Publication City/Country Cambridge, United States Language English Illustrations note 15 color illus., 36 b&w illus.; 51 Illustrations, unspecified ISBN10 0262037319 ISBN13 9780262037310 Bestsellers rank 321,497

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