logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Bayesian Networks: An Introduction (Wiley Series in Probability and Statistics) by Timo Koski, John Noble ISBN 9780470743041, 0470743042

  • SKU: EBN-1293270
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.6

38 reviews
Instant download (eBook) Bayesian Networks: An Introduction (Wiley Series in Probability and Statistics) after payment.
Authors:Timo Koski, John Noble
Pages:368 pages.
Year:2009
Editon:1
Publisher:Wiley
Language:english
File Size:1.91 MB
Format:pdf
ISBNS:9780470743041, 0470743042
Categories: Ebooks

Product desciption

(Ebook) Bayesian Networks: An Introduction (Wiley Series in Probability and Statistics) by Timo Koski, John Noble ISBN 9780470743041, 0470743042

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout.Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products