Elements of Causal Inference: Foundations and Learning Algorithms

by Jonas Peters, Bernhard Scholkopf, Dominik Janzing, et al.

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...

• Format: Hardcover
• Language: English
• ISBN: 0262037319
• ISBN13: 9780262037310
• Release Date: November 2017
• Publisher: MIT Press
• Length: 288 Pages
• Weight: 1.55 lbs.
• Dimensions: 0.9" x 7.2" x 9.0"
• Age Range: 18 years and up
• Grade Range: Postsecondary and higher