Logo

Elements of Causal Inference: Foundations and Learning Algorithms

Large book cover: Elements of Causal Inference: Foundations and Learning Algorithms

Elements of Causal Inference: Foundations and Learning Algorithms
by

Publisher: The MIT Press
ISBN-13: 9780262037310
Number of pages: 289

Description:
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.

Home page url

Download or read it online for free here:
Download link
(21MB, PDF)

Similar books

Book cover: A First Encounter with Machine LearningA First Encounter with Machine Learning
by - University of California Irvine
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(11969 views)
Book cover: Machine Learning for DesignersMachine Learning for Designers
by - O'Reilly Media
This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.
(6662 views)
Book cover: Inductive Logic Programming: Theory and MethodsInductive Logic Programming: Theory and Methods
by - ScienceDirect
Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. The authors survey the most important theories and methods of this new field.
(35140 views)
Book cover: Understanding Machine Learning: From Theory to AlgorithmsUnderstanding Machine Learning: From Theory to Algorithms
by - Cambridge University Press
This book introduces machine learning and the algorithmic paradigms it offers. It provides a theoretical account of the fundamentals underlying machine learning and mathematical derivations that transform these principles into practical algorithms.
(10030 views)