Uncertainty - Lecture 2 - CS50's Introduction to Artificial Intelligence with Python 2020
00:00:00 - Introduction
00:00:15 - Uncertainty
00:04:52 - Probability
00:09:37 - Conditional Probability
00:17:19 - Random Variables
00:26:28 - Bayes' Rule
00:34:01 - Joint Probability
00:40:13 - Probability Rules
00:49:42 - Bayesian Networks
01:21:00 - Sampling
01:32:58 - Markov Models
01:44:17 - Hidden Markov Models
This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposu…
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Chapters (12)
Introduction
0:15
Uncertainty
4:52
Probability
9:37
Conditional Probability
17:19
Random Variables
26:28
Bayes' Rule
34:01
Joint Probability
40:13
Probability Rules
49:42
Bayesian Networks
1:21:00
Sampling
1:32:58
Markov Models
1:44:17
Hidden Markov Models
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