Parameter learning 1: Maximum likelihood estimation скачать в хорошем качестве

Parameter learning 1: Maximum likelihood estimation

00:00 Reviewing the previous chapter 00:59 Parameter learning: example 02:03 Recall: The likelihood function 3:50 Maximum likelihood estimation (MLE) 7:54 Example 15:42 Parameter learning for Bayesian networks 21:41 See it in practice Authors: Hamid Kalantari, Pouria Ramazi Instructor: Pouria Ramazi Thank you Arezoo Haratian, Julia Schmid, and Amit Chakraborty for helping with revising the slides. This project is made possible with funding by the Government of Ontario and through eCampusOntario's support of the Virtual Learning Strategy. To learn more about the Virtual Learning Strategy visit: https://vls.ecampusontario.ca This work is licensed under a Creative Commons “Attribution-NonCommercial 4.0 International” license.