Graphical models and causal discovery with Python : 100 exercises for building logic /

Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical inference, and graph theory, the book offers a systematic pathway from foundational principles...

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Bibliographic Details
Main Author:	Suzuki, Joe (Author)
Format:	eBook
Language:	English
Published:	Singapore : Springer, 2026.
Subjects:	Graphical modeling (Statistics) Python (Computer program language) Modèles graphiques (Statistique) Python (Langage de programmation) Electronic books.

Table of Contents:

A Gentle Introduction to Causal Discovery
Foundations of Probability and Statistics
Graphical Models
Testing Independence and Conditional Independence with Kernels
The PC Algorithm
LiNGAM
Information Criteria and Marginal Likelihood
Score-Based Structure Learning.