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Lecture 19 Conclusion | Stanford CS221 AI Autumn 2019

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Lessons List | 19 Lesson
Lecture 1 Overview | Stanford CS221 AI Autumn 2019
01:27:26

Lecture 1 Overview | Stanford CS221 AI Autumn 2019
Lecture 2 Machine Learning 1 Linear Classifiers SGD | Stanford CS221 AI Autumn 2019
01:20:34

Lecture 2 Machine Learning 1 Linear Classifiers SGD | Stanford CS221 AI Autumn 2019
Lecture 3 Machine Learning 2 Features Neural Networks | Stanford CS221 AI Autumn 2019
01:22:23

Lecture 3 Machine Learning 2 Features Neural Networks | Stanford CS221 AI Autumn 2019
Lecture 4 Machine Learning 3 Generalization K means | Stanford CS221 AI Autumn 2019
01:23:07

Lecture 4 Machine Learning 3 Generalization K means | Stanford CS221 AI Autumn 2019
Lecture 5 Search 1 Dynamic Programming Uniform Cost Search | Stanford CS221 AI Autumn 2019
01:20:25

Lecture 5 Search 1 Dynamic Programming Uniform Cost Search | Stanford CS221 AI Autumn 2019
Lecture 6 Search 2 A | Stanford CS221 AI Autumn 2019
01:21:54

Lecture 6 Search 2 A | Stanford CS221 AI Autumn 2019
Lecture 7 Markov Decision Processes Value Iteration | Stanford CS221 AI Autumn 2019
01:23:07

Lecture 7 Markov Decision Processes Value Iteration | Stanford CS221 AI Autumn 2019
Lecture 8 Markov Decision Processes Reinforcement Learning | Stanford CS221 AI Autumn 2019
01:14:38

Lecture 8 Markov Decision Processes Reinforcement Learning | Stanford CS221 AI Autumn 2019
Lecture 9 Game Playing 1 Minimax Alpha beta Pruning | Stanford CS221 AI Autumn 2019
01:21:33

Lecture 9 Game Playing 1 Minimax Alpha beta Pruning | Stanford CS221 AI Autumn 2019
Lecture 10 Game Playing 2 TD Learning Game Theory | Stanford CS221 AI Autumn 2019
01:19:26

Lecture 10 Game Playing 2 TD Learning Game Theory | Stanford CS221 AI Autumn 2019
Lecture 11 Factor Graphs 1 Constraint Satisfaction Problems | Stanford CS221 AI Autumn 2019
01:21:17

Lecture 11 Factor Graphs 1 Constraint Satisfaction Problems | Stanford CS221 AI Autumn 2019
Lecture 12 Factor Graphs 2 Conditional Independence | Stanford CS221 AI Autumn 2019
01:17:51

Lecture 12 Factor Graphs 2 Conditional Independence | Stanford CS221 AI Autumn 2019
Lecture 13 Bayesian Networks 1 Inference | Stanford CS221 AI Autumn 2019
01:21:39

Lecture 13 Bayesian Networks 1 Inference | Stanford CS221 AI Autumn 2019
Lecture 14 Bayesian Networks 2 Forward Backward | Stanford CS221 AI Autumn 2019
01:11:49

Lecture 14 Bayesian Networks 2 Forward Backward | Stanford CS221 AI Autumn 2019
Lecture 15 Bayesian Networks 3 Maximum Likelihood | Stanford CS221 AI Autumn 2019
01:23:45

Lecture 15 Bayesian Networks 3 Maximum Likelihood | Stanford CS221 AI Autumn 2019
Lecture 16 Logic 1 Propositional Logic | Stanford CS221 AI Autumn 2019
01:18:33

Lecture 16 Logic 1 Propositional Logic | Stanford CS221 AI Autumn 2019
Lecture 17 Logic 2 First order Logic | Stanford CS221 AI Autumn 2019
01:19:55

Lecture 17 Logic 2 First order Logic | Stanford CS221 AI Autumn 2019
Lecture 18 Deep Learning | Stanford CS221 AI Autumn 2019
01:12:57

Lecture 18 Deep Learning | Stanford CS221 AI Autumn 2019
Lecture 19 Conclusion | Stanford CS221 AI Autumn 2019
01:01:48

Lecture 19 Conclusion | Stanford CS221 AI Autumn 2019

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Course Description

What are the four key principles of responsible AI? Answer: Their principles underscore fairness, transparency and explainability, human-centeredness, and privacy and security.Artificial intelligence is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.What is artificial intelligence with examples? Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans. For example, speech recognition, problem-solving, learning and planning.What are the 4 types of AI? An Introduction to Artificial Intelligence: The Four Types of AI Reactive Machines. Reactive machines are the simplest level of robot. ... Limited Memory. A limited memory machine, as the name might suggest, is able to retain some information learned from observing previous events or data. ... Theory of Mind. ... Self-awareness.
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