Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Probabilistic Graphical Models: Principles And ApplicationsISBN13:9783030619459ISBN10:3030619451Author:Sucar, Luis Enrique (Author)Description:Part I: Fundamentalsintroductionprobability Theorygraph Theorypart Ii: Probabilistic Modelsbayesian Classifiershidden Markov Modelsmarkov Random Fieldsbayesian Networks: Representation And Inferencebayesian Networks: Learningdynamic And Temporal Bayesian Networkspart Iii: Decision Modelsdecision Graphsmarkov Decision Processespartially Observable Markov Decision Processes Part Iv: Relational, Causal And Deep Modelsrelational Probabilistic Graphical Modelsgraphical Causal Modelscausal Discoverydeep Learning And Graphical Modelsa: A Python Library For Inference And Learningglossaryindex Binding:Paperback, PaperbackPublisher:SpringerPublication Date:2021-12-24Weight:1.18 lbsDimensions:0.79'' H x 9.21'' L x 6.14'' WNumber of Pages:384Language:English
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Book Title: Probabilistic Graphical Models: Principles And Applications
Item Length: 9.3in
Item Width: 6.1in
Author: Luis Enrique Sucar
Publication Name: Probabilistic Graphical Models : Principles and Applications
Format: Trade Paperback
Language: English
Publisher: Springer International Publishing A&G
Series: Advances in Computer Vision and Pattern Recognition Ser.
Publication Year: 2021
Type: Textbook
Item Weight: 20.7 Oz
Number of Pages: Xxviii, 355 Pages
