Sep 28, 2020  
Rensselaer Catalog 2018-2019 
    
Rensselaer Catalog 2018-2019 [Archived Catalog]

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ECSE 4810 - Introduction to Probabilistic Graphical Models


This course covers topics related to learning and inference with different types of Probabilistic Graphical Models (PGMs). It also demonstrates the application of PGMs to different fields. The course covers both directed and undirected graphical models, both parameter and structure learning, and both exact and approximated inference methods.

Prerequisites/Corequisites: Prerequisites: ECSE 2500 or equivalent and proficiency in computer programming. Prior knowledge in pattern recognition or machine learning is a plus but is not required.

When Offered: Fall term even-numbered years.



Cross Listed: ECSE 6810. Students cannot receive credit for both this course and ECSE 6810.

Credit Hours: 3



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