Engineering Probability Lecture 16: Conditional PDFs; Bayesian and maximum likelihood estimation
1,849 views · Published 19 November 2018 · 1:10:10 · Indexed 17 October 2026
Channel: Rich Radke · 2018 · Education
ECSE-2500 Engineering Probability Rich Radke, Rensselaer Polytechnic Institute Lecture 16: Conditional PDFs; Bayesian and maximum likelihood estimation (11/15/18) Follows Sections 5.7.1, 8.3, and 8.6 of the textbook (Leon-Garcia, 3rd ed.).
More from this channel
-
39:02
CVFX Lecture 11: Feature evaluation and use
-
56:48
CVFX Lecture 20: Motion capture setup and forward kinematics
-
47:47
Computer Vision: From Rensselaer to Hollywood
-
1:04:32
Engineering Probability Lecture 7: Conditional probability mass functions
-
46:14
Engineering Probability Lecture 8: Cumulative distribution functions (CDFs)
-
57:14
Engineering Probability Lecture 10: The Gaussian random variable and Q function
-
41:06
Engineering Probability Lecture 12: Functions of a random variable; inequalities
-
1:04:47
Engineering Probability Lecture 13: Two random variables (discrete)