Graphical Models and Causal Discovery with Python by Joe Suzuki(.PDF)+
File Size: 34.3 MB
Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic by Joe Suzuki
Requirements: .ePUB, .PDF reader, 34.3 MB | True PDF, True EPUB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
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