Graphical Models and Causal Discovery with Python [#1032515]

Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic
English | 2026 | ISBN: 9819553075 | 202 Pages | PDF EPUB (True) | 30 MB
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 to cutting-edge algorithms, including independence tests, the PC algorithm, LiNGAM, information criteria, and Bayesian methods. Far more than a theoretical treatment, this volume emphasizes hands-on learning through Python implementations, carefully designed exercises with solutions, and intuitive graphical illustrations. Readers will gain the ability to see, run, and understand causal discovery methods in practice.