Bernhard (Director of the Max Planck Institute for Intelligent in Tubingen, Germany, Professor for Machine Lea, Max Plan
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...
The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. Th...
