Chapter 25. Learning from Observations 7.8 - 25.5. Evaluating and Choosing the Best Hypothesis (Part 2)/ClipID:30376 previous clip next clip

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Recording date 2021-03-30
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Course

Artificial Intelligence (AI-2) SS 2021

Lecturer

Prof. Dr. Michael Kohlhase

Via

Free

Language

English

Organisational Unit

Professur für Wissensrepräsentation und -verarbeitung

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

Format

lecture

Type

university lecture

Definition of different loss functions and the concept of regularization. Also, the Minimal Description Length and the scale of Machine Learning is discussed. 

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Chapter 25. Learning from Observations 7.9 - 25.6. Computational Learning Theory (Part 1)
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Chapter 25. Learning from Observations 7.10 - 25.6. Computational Learning Theory (Part 2)
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Chapter 25. Learning from Observations 7.11 - 25.7. Regression and Classification with Linear Models (Part 1)
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Chapter 25. Learning from Observations 7.12 - 25.7. Regression and Classification with Linear Models (Part 2)
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Chapter 25. Learning from Observations 7.13 - 25.7. Regression and Classification with Linear Models (Part 3)
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