Name: Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic (en Inglés)
Price: 202.81 PEN
Availability: InStock
Author: Suzuki, Joe
ISBN: 9789819553075

portada Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic (en Inglés)

Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Suzuki, Joe

Idioma

Inglés

N° páginas

193

Encuadernación

Tapa Blanda

ISBN13

9789819553075

Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic (en Inglés)

Suzuki, Joe (Autor) · Springer · Tapa Blanda

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Reseña del libro "Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic (en Inglés)"

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. Key features of this book include: A clear and self-contained introduction, bridging probability, statistics, and modern causal discovery techniques 100 exercises with solutions, supporting self-study and classroom use Reproducible Python code, allowing readers to implement and extend the methods themselves Intuitive figures and visual explanations that clarify abstract concepts Broad coverage of applications within statistics and data science, connecting rigorous theory with modern machine learning and causal inference