Artificial Intelligence (AI-2) SS 2021 /CourseID:2095

Detailed information

Most recent entry on 2021-05-10 

Lecturer

Prof. Dr. Michael Kohlhase

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Recording type

Vorlesungsreihe

Via

Free

Language

English

The second semester of the general AI course at FAU, held Summer Semester 2021.

Course chapters

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Recap Clip 3.1: Sources of Uncertainty preview image
Recap Clip 3.1: Sources of Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:20
go to clip page
2
Recap Clip 3.2: Recap: Rational Agents as a Conceptual Framework preview image
Recap Clip 3.2: Recap: Rational Agents as a Conceptual Framework
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:34
go to clip page
3
Recap Clip 3.3: Agent Architectures based on Belief States preview image
Recap Clip 3.3: Agent Architectures based on Belief States
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:38
go to clip page
4
Recap Clip 3.4: Modeling Uncertainty preview image
Recap Clip 3.4: Modeling Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:52
go to clip page
5
Recap Clip 3.5: Acting Under Uncertainty preview image
Recap Clip 3.5: Acting Under Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:38
go to clip page
6
Recap Clip 3.6: Agenda for this Chapter: Basics of Probability Theory preview image
Recap Clip 3.6: Agenda for this Chapter: Basics of Probability Theory
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:07
go to clip page
7
Recap Clip 3.7: Unconditional Probabilities (Part 1) preview image
Recap Clip 3.7: Unconditional Probabilities (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:26
go to clip page
8
Recap Clip 3.8: Unconditional Probabilities (Part 2) preview image
Recap Clip 3.8: Unconditional Probabilities (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:58
go to clip page
9
Recap Clip 3.9: Conditional Probabilities preview image
Recap Clip 3.9: Conditional Probabilities
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:21
go to clip page
10
Recap Clip 3.10: Independence preview image
Recap Clip 3.10: Independence
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:40
go to clip page
11
Recap Clip 3.11: Basic Probabilistic Reasoning Methods preview image
Recap Clip 3.11: Basic Probabilistic Reasoning Methods
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:12:07
go to clip page
12
Recap Clip 3.12: Bayes' Rule preview image
Recap Clip 3.12: Bayes' Rule
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:26
go to clip page
13
Recap Clip 3.13: Conditional Independence preview image
Recap Clip 3.13: Conditional Independence
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:11
go to clip page
14
Recap Clip 4.1: Introduction preview image
Recap Clip 4.1: Introduction
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:41
go to clip page
15
Recap Clip 4.2: What is a Bayesian Network? preview image
Recap Clip 4.2: What is a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:12
go to clip page
16
Recap Clip 4.3: What is the Meaning of a Bayesian Network? preview image
Recap Clip 4.3: What is the Meaning of a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:33
go to clip page
17
Recap Clip 4.4: Constructing Bayesian Networks (Part 1) preview image
Recap Clip 4.4: Constructing Bayesian Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:52
go to clip page
18
Recap Clip 4.5: Constructing Bayesian Networks (Part 2) preview image
Recap Clip 4.5: Constructing Bayesian Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:17
go to clip page
19
Recap Clip 4.6: Inference in Bayesian Networks preview image
Recap Clip 4.6: Inference in Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:55
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20
Recap Clip 4.7: Conclusion preview image
Recap Clip 4.7: Conclusion
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:57
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21
Recap Clip 5.1: Introduction preview image
Recap Clip 5.1: Introduction
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:08
go to clip page
22
Recap Clip 5.2: Rational Preferences preview image
Recap Clip 5.2: Rational Preferences
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:04
go to clip page
23
Recap Clip 5.3: Utilities and Money (Part 1) preview image
Recap Clip 5.3: Utilities and Money (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:51
go to clip page
24
Recap Clip 5.4: Utilities and Money (Part 2) preview image
Recap Clip 5.4: Utilities and Money (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:00
go to clip page
25
Recap Clip 5.5: Multi-Attribute Utility (Part 1) preview image
Recap Clip 5.5: Multi-Attribute Utility (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:03
go to clip page
26
Recap Clip 5.6: Multi-Attribute Utility (Part 2) preview image
Recap Clip 5.6: Multi-Attribute Utility (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:38
go to clip page
27
Recap Clip 5.7: Decision Networks preview image
Recap Clip 5.7: Decision Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:14:48
go to clip page
28
Recap Clip 6.?: Modeling Time and Uncertainty preview image
Recap Clip 6.?: Modeling Time and Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:11
go to clip page
29
Recap Clip 6.3: Inference: Filtering, Prediction and Smoothing (Part 1) preview image
Recap Clip 6.3: Inference: Filtering, Prediction and Smoothing (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:57
go to clip page
30
Recap Clip 6.4: Inference: Filtering, Prediction and Smoothing (Part 2) preview image
Recap Clip 6.4: Inference: Filtering, Prediction and Smoothing (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:32
go to clip page
31
Recap Clip 6.5: Inference: Filtering, Prediction and Smoothing (Part 3) preview image
Recap Clip 6.5: Inference: Filtering, Prediction and Smoothing (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:06
go to clip page
32
Recap Clip 6.6: Hidden Markov Models (Part 1) preview image
Recap Clip 6.6: Hidden Markov Models (Part 1)
Dennis Müller
2021-03-30
Free
00:08:14
go to clip page
33
Recap Clip 6.7: Hidden Markov Models (Part 2) preview image
Recap Clip 6.7: Hidden Markov Models (Part 2)
Dennis Müller
2021-03-30
Free
00:10:39
go to clip page
34
Recap Clip 6.8: Dynamic Bayesian Networks preview image
Recap Clip 6.8: Dynamic Bayesian Networks
Dennis Müller
2021-03-30
Free
00:07:19
go to clip page
35
Recap Clip 7.1: Making Complex Decisions preview image
Recap Clip 7.1: Making Complex Decisions
Dennis Müller
2021-03-30
Free
00:01:23
go to clip page
36
Recap Clip 7.2: Sequential Decision Problems preview image
Recap Clip 7.2: Sequential Decision Problems
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:07
go to clip page
37
Recap Clip 7.4: Value/Policy Iteration preview image
Recap Clip 7.4: Value/Policy Iteration
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:42
go to clip page
38
Recap Clip 7.5: Partially Observable MDPs preview image
Recap Clip 7.5: Partially Observable MDPs
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:16
go to clip page
39
Recap Clip 7.6: Online Agents with POMDPs preview image
Recap Clip 7.6: Online Agents with POMDPs
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:15
go to clip page
40
Recap Clip 8.2: Forms of Learning preview image
Recap Clip 8.2: Forms of Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:22
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41
Recap Clip 8.3: Inductive Learning preview image
Recap Clip 8.3: Inductive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:58
go to clip page
42
Recap Clip 8.4: Learning Decision Trees preview image
Recap Clip 8.4: Learning Decision Trees
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:35
go to clip page
43
Recap Clip 8.5: Using Information Theory (Part 1) preview image
Recap Clip 8.5: Using Information Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:10
go to clip page
44
Recap Clip 8.6: Using Information Theory (Part 2) preview image
Recap Clip 8.6: Using Information Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:23
go to clip page
45
Recap Clip 8.7: Evaluating and Choosing the Best Hypothesis (Part 1) preview image
Recap Clip 8.7: Evaluating and Choosing the Best Hypothesis (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:10
go to clip page
46
Recap Clip 8.8: Evaluating and Choosing the Best Hypothesis (Part 2) preview image
Recap Clip 8.8: Evaluating and Choosing the Best Hypothesis (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:40
go to clip page
47
Recap Clip 8.9: Computational Learning Theory (Part 1) preview image
Recap Clip 8.9: Computational Learning Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:01
go to clip page
48
Recap Clip 8.10: Computational Learning Theory (Part 2) preview image
Recap Clip 8.10: Computational Learning Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:04
go to clip page
49
Recap Clip 8.11: Regression and Classification with Linear Models (Part 1) preview image
Recap Clip 8.11: Regression and Classification with Linear Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:31
go to clip page
50
Recap Clip 8.12: Regression and Classification with Linear Models (Part 2) preview image
Recap Clip 8.12: Regression and Classification with Linear Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:30
go to clip page
51
Recap Clip 8.13: Regression and Classification with Linear Models (Part 3) preview image
Recap Clip 8.13: Regression and Classification with Linear Models (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:55
go to clip page
52
Recap Clip 8.14: Artificial Neural Networks (Part 1) preview image
Recap Clip 8.14: Artificial Neural Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:49
go to clip page
53
Recap Clip 8.15: Artificial Neural Networks (Part 2) preview image
Recap Clip 8.15: Artificial Neural Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:12
go to clip page
54
Recap Clip 8.16: Artificial Neural Networks (Part 3) preview image
Recap Clip 8.16: Artificial Neural Networks (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:23
go to clip page
55
Recap Clip 8.17: Artificial Neural Networks (Part 4) preview image
Recap Clip 8.17: Artificial Neural Networks (Part 4)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:24
go to clip page
56
Recap Clip 8.18: Support Vector Machines preview image
Recap Clip 8.18: Support Vector Machines
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:12:16
go to clip page
57
Recap Clip 9.1: Full Bayesian Learning preview image
Recap Clip 9.1: Full Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:41
go to clip page
58
Recap Clip 10.1: Logical Formulations of Learning (Part 1) preview image
Recap Clip 10.1: Logical Formulations of Learning (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:52
go to clip page
59
Recap Clip 10.2: Logical Formulations of Learning (Part 2) preview image
Recap Clip 10.2: Logical Formulations of Learning (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:00:58
go to clip page
60
Recap Clip 10.3: Explanation-Based Learning preview image
Recap Clip 10.3: Explanation-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:26
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61
Recap Clip 10.4: Relevance-Based Learning preview image
Recap Clip 10.4: Relevance-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:13:33
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62
Recap Clip 10.5: Inductive Logic Programming: An Example preview image
Recap Clip 10.5: Inductive Logic Programming: An Example
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:44
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63
Recap Clip 10.7: Inductive Logic Programming: Inverse Resolution preview image
Recap Clip 10.7: Inductive Logic Programming: Inverse Resolution
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:56
go to clip page
64
Recap Clip 11.1: Reinforcement Learning: Introduction & Motivation preview image
Recap Clip 11.1: Reinforcement Learning: Introduction & Motivation
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:29
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Episode
Title
Lecturer
Updated
Via
Duration
Media
3
Lecture1. Admin/Overview preview image
Lecture1. Admin/Overview
Prof. Dr. Michael Kohlhase
2021-04-13
Free
01:31:38
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
20.1.1. Sources of Uncertainty preview image
20.1.1. Sources of Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-11
Free
00:07:35
go to clip page
2
20.1.2. Recap: Rational Agents as a Conceptual Framework preview image
20.1.2. Recap: Rational Agents as a Conceptual Framework
Prof. Dr. Michael Kohlhase
2021-01-11
Free
00:14:27
go to clip page
3
20.1.3. Agent Architectures based on Belief States preview image
20.1.3. Agent Architectures based on Belief States
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:14:08
go to clip page
4
20.1.4. Modeling Uncertainty preview image
20.1.4. Modeling Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:28:00
go to clip page
5
20.1.5. Acting Under Uncertainty preview image
20.1.5. Acting Under Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:11:56
go to clip page
6
20.1.6. Agenda for this Chapter: Basics of Probability Theory preview image
20.1.6. Agenda for this Chapter: Basics of Probability Theory
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:01:56
go to clip page
7
20.2. Unconditional Probabilities (Part 1) preview image
20.2. Unconditional Probabilities (Part 1)
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:17:31
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8
20.2. Unconditional Probabilities (Part 2) preview image
20.2. Unconditional Probabilities (Part 2)
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:23:25
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9
20.3. Conditional Probabilities preview image
20.3. Conditional Probabilities
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:07:55
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10
20.4. Independence preview image
20.4. Independence
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:17:28
go to clip page
11
20.5. Basic Probabilistic Reasoning Methods preview image
20.5. Basic Probabilistic Reasoning Methods
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:22:22
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12
20.6. Bayes' Rule preview image
20.6. Bayes' Rule
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:13:52
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13
20.7. Conditional Independence preview image
20.7. Conditional Independence
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:32:10
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14
20.8. The Wumpus World Revisited preview image
20.8. The Wumpus World Revisited
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:14:18
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15
20.9. Conclusion preview image
20.9. Conclusion
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:01:46
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
21.1. Introduction preview image
21.1. Introduction
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:04:10
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2
21.2. What is a Bayesian Network? preview image
21.2. What is a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:22:47
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3
21.3. What is the Meaning of a Bayesian Network? preview image
21.3. What is the Meaning of a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:15:22
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4
21.4. Constructing Bayesian Networks (Part 1) preview image
21.4. Constructing Bayesian Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:20:13
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5
21.4. Constructing Bayesian Networks (Part 2) preview image
21.4. Constructing Bayesian Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:26:48
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6
21.5. Inference in Bayesian Networks preview image
21.5. Inference in Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:25:50
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7
21.6. Conclusion preview image
21.6. Conclusion
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:07:58
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
22.1. Introduction preview image
22.1. Introduction
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:17:29
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2
22.2 Rational Preferences preview image
22.2 Rational Preferences
Prof. Dr. Michael Kohlhase
2021-05-09
Free
00:12:36
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3
22.3. Utilities and Money (Part 1) preview image
22.3. Utilities and Money (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:14:04
go to clip page
4
22.3. Utilities and Money (Part 2) preview image
22.3. Utilities and Money (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:16:57
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5
22.4. Multi-Attribute Utility (Part 1) preview image
22.4. Multi-Attribute Utility (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:29:12
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6
22.4. Multi-Attribute Utility (Part 2) preview image
22.4. Multi-Attribute Utility (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:14:42
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7
22.5. Decision Networks preview image
22.5. Decision Networks
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:24:07
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8
22.6. The Value of Information (Part 1) preview image
22.6. The Value of Information (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:17:01
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9
22.6. The Value of Information (Part 2) preview image
22.6. The Value of Information (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:18:20
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
23.1 Time and Uncertainty preview image
23.1 Time and Uncertainty
Prof. Dr. Michael Kohlhase
2021-05-10
Free
00:27:22
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2
23.2. Inference: Filtering, Prediction and Smoothing (Part 1) preview image
23.2. Inference: Filtering, Prediction and Smoothing (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:29:04
go to clip page
3
23.2. Inference: Filtering, Prediction and Smoothing (Part 2) preview image
23.2. Inference: Filtering, Prediction and Smoothing (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:23:41
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4
23.2. Inference: Filtering, Prediction and Smoothing (Part 3) preview image
23.2. Inference: Filtering, Prediction and Smoothing (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:11:54
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5
23.3. Hidden Markov Models (Part 1) preview image
23.3. Hidden Markov Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:21:07
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6
23.3. Hidden Markov Models (Part 2) preview image
23.3. Hidden Markov Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:18:56
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7
23.4. Dynamic Bayesian Networks preview image
23.4. Dynamic Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:12:37
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
24. Making Complex Decisions preview image
24. Making Complex Decisions
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:03:10
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2
24.1. Sequential Decision Problems preview image
24.1. Sequential Decision Problems
Dennis Müller
2021-03-29
Free
00:11:56
go to clip page
3
24.2. Utilities over Time preview image
24.2. Utilities over Time
Dennis Müller
2021-03-29
Free
00:21:54
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4
24.3. Value/Policy Iteration preview image
24.3. Value/Policy Iteration
Dennis Müller
2021-03-29
Free
00:21:05
go to clip page
5
24.4. Partially Observable MDPs preview image
24.4. Partially Observable MDPs
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:20:42
go to clip page
6
24.5. Online Agents with POMDPs preview image
24.5. Online Agents with POMDPs
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:21:57
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
25. Learning from Observations preview image
25. Learning from Observations
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:49
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2
25.1. Forms of Learning preview image
25.1. Forms of Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:26
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3
25.2. Inductive Learning preview image
25.2. Inductive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:43
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4
25.3. Learning Decision Trees preview image
25.3. Learning Decision Trees
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:33
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5
25.4. Using Information Theory (Part 1) preview image
25.4. Using Information Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:27:33
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6
25.4. Using Information Theory (Part 2) preview image
25.4. Using Information Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:26:53
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7
25.5. Evaluating and Choosing the Best Hypothesis (Part 1) preview image
25.5. Evaluating and Choosing the Best Hypothesis (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:22:00
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8
25.5. Evaluating and Choosing the Best Hypothesis (Part 2) preview image
25.5. Evaluating and Choosing the Best Hypothesis (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:31:59
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9
25.6. Computational Learning Theory (Part 1) preview image
25.6. Computational Learning Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:25:36
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10
25.6. Computational Learning Theory (Part 2) preview image
25.6. Computational Learning Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:15:22
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11
25.7. Regression and Classification with Linear Models (Part 1) preview image
25.7. Regression and Classification with Linear Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:46
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12
25.7. Regression and Classification with Linear Models (Part 2) preview image
25.7. Regression and Classification with Linear Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:21
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13
25.7. Regression and Classification with Linear Models (Part 3) preview image
25.7. Regression and Classification with Linear Models (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:04
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14
25.8. Artificial Neural Networks (Part 1) preview image
25.8. Artificial Neural Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:19:21
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15
25.8. Artificial Neural Networks (Part 2) preview image
25.8. Artificial Neural Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:59
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16
25.8. Artificial Neural Networks (Part 3) preview image
25.8. Artificial Neural Networks (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:16:59
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17
25.8. Artificial Neural Networks (Part 4) preview image
25.8. Artificial Neural Networks (Part 4)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:09
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18
25.9. Support Vector Machines preview image
25.9. Support Vector Machines
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:28:28
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19
Bonus: Science Slam preview image
Bonus: Science Slam
Jonas Betzendahl
2021-03-30
Free
00:12:41
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
26.1. Full Bayesian Learning preview image
26.1. Full Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:13:26
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2
26.2. Approximations of Bayesian Learning preview image
26.2. Approximations of Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:14:58
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3
26.3. Parameter Learning for Bayesian Networks preview image
26.3. Parameter Learning for Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:25
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4
26.4. Naive Bayes Models preview image
26.4. Naive Bayes Models
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:19
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Episode
Title
Lecturer
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Duration
Media
1
27.1. Logical Formulations of Learning (Part 1) preview image
27.1. Logical Formulations of Learning (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:00
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2
27.1. Logical Formulations of Learning (Part 2) preview image
27.1. Logical Formulations of Learning (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:38
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3
27.2. Explanation-Based Learning preview image
27.2. Explanation-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:32:40
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4
27.3. Relevance-Based Learning preview image
27.3. Relevance-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:26:56
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5
27.4.1. Inductive Logic Programming: An Example preview image
27.4.1. Inductive Logic Programming: An Example
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:40
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6
27.4.2. Inductive Logic Programming: Top-Down Inductive Learning: FOIL preview image
27.4.2. Inductive Logic Programming: Top-Down Inductive Learning: FOIL
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:48
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7
27.4.3. Inductive Logic Programming: Inverse Resolution preview image
27.4.3. Inductive Logic Programming: Inverse Resolution
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:22
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Episode
Title
Lecturer
Updated
Via
Duration
Media
1
28.1. Reinforcement Learning: Introduction & Motivation preview image
28.1. Reinforcement Learning: Introduction & Motivation
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:14
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2
28.2. Passive Learning preview image
28.2. Passive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:10:46
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Episode
Title
Lecturer
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Media
1
31. What did we learn in AI 1/2? (Part 1) preview image
31. What did we learn in AI 1/2? (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:27:11
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2
31. What did we learn in AI 1/2? (Part 2) preview image
31. What did we learn in AI 1/2? (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:19:14
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