Mastering Probabilistic Graphical Model

Modeling and Analysis of Dependable Systems: A Probabilistic Graphical Model Perspective

Modeling and Analysis of Dependable Systems: A Probabilistic Graphical Model Perspective by Luigi Portinale and Daniele Codetta Raiteri
English | 2015 | ISBN: 9814612030 | 272 pages | PDF | 6,4 MB
Mastering Probabilistic Graphical Models Using Python (Repost)

Mastering Probabilistic Graphical Models Using Python By Ankur Ankan, Abinash Panda
2015 | 284 Pages | ISBN: 1784394688 | PDF | 17 MB

Mastering Probabilistic Graphical Models using Python  

Posted by AlenMiler at Aug. 13, 2015
Mastering Probabilistic Graphical Models using Python

Mastering Probabilistic Graphical Models using Python by Ankur Ankan
English | 26 July 2015 | ISBN: 1784394688 | 284 Pages | EPUB/MOBI/PDF (True) | 34.35 MB
With: Code Files

If you are a researcher or a machine learning enthusiast, or are working in the data science field and have a basic idea of Bayesian learning or probabilistic graphical models, this book will help you to understand the details of graphical models and use them in your data science problems.

Coursera: Probabilistic Graphical Models  eBooks & eLearning

Posted by ParRus at Feb. 17, 2016
Coursera: Probabilistic Graphical Models

Coursera: Stanford University - Probabilistic Graphical Models
WEBRip | English | MP4 + PDF Slides | 960 x 540 | AVC ~39.6 kbps | 15 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 23:25:47 | 1.36 GB
Genre: eLearning Video / Computer Science, Engineering and Technology

What are Probabilistic Graphical Models? Uncertainty is unavoidable in real-world applications: we can almost never predict with certainty what will happen in the future, and even in the present and the past, many important aspects of the world are not observed with certainty. Probability theory gives us the basic foundation to model our beliefs about the different possible states of the world, and to update these beliefs as new evidence is obtained. These beliefs can be combined with individual preferences to help guide our actions, and even in selecting which observations to make. While probability theory has existed since the 17th century, our ability to use it effectively on large problems involving many inter-related variables is fairly recent, and is due largely to the development of a framework known as Probabilistic Graphical Models (PGMs).

Building Probabilistic Graphical Models with Python (Repost)  eBooks & eLearning

Posted by DZ123 at Dec. 10, 2016
Building Probabilistic Graphical Models with Python (Repost)

Kiran R Karkera, "Building Probabilistic Graphical Models with Python"
English | 2014 | ISBN: 1783289007 | PDF | pages: 173 | 8.3 mb

Building Probabilistic Graphical Models with Python (repost)  eBooks & eLearning

Posted by interes at June 12, 2016
Building Probabilistic Graphical Models with Python (repost)

Building Probabilistic Graphical Models with Python by Kiran R Karkera
English | 2014 | ISBN: 1783289007 | 172 pages | PDF | 4,3 MB

Learning Probabilistic Graphical Models in R  eBooks & eLearning

Posted by Grev27 at May 14, 2016
Learning Probabilistic Graphical Models in R

David Bellot, "Learning Probabilistic Graphical Models in R"
English | ISBN: 1784392057 | 2016 | PDF/EPUB/MOBI | 250 pages | 4 MB/7 MB/11 MB
Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition) (Repost)

Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition) By Luis Enrique Sucar
2015 | 267 Pages | ISBN: 1447166981 | PDF | 6 MB
Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition) (Repost)

Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition) By Luis Enrique Sucar
2015 | 267 Pages | ISBN: 1447166981 | PDF | 8 MB
Probabilistic Graphical Models: Principles and Applications (Repost)

Luis Enrique Sucar, "Probabilistic Graphical Models: Principles and Applications"
English | ISBN: 1447166981 | 2015 | 280 pages | True PDF | 9 MB