Ship to
Austria
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic
Type
Physical Book
Publisher
Author
Language
English
Pages
193
Format
Paperback
ISBN13
9789819553075

Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic

Suzuki, Joe (Author) · Springer · Paperback

Graphical Models and Causal Discovery with Python: 100 Exercises for Building Logic - Suzuki, Joe

Cheaper New Book Imported to Austria
Delivery: 25 Aug - 02 Sep Shipping: 16 to 20 business days.
63,33 €
Faster New Book Imported to Austria
Delivery: 05 Aug - 06 Aug Shipping: 2 to 2 business days.
71,65 €
Import costs and 10% VAT included in the price ✅
63,33 €

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "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 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

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews