Presenter(s): Marco Puts & Piet Daas (CBS), CBS
e-mail(s):
Date: 11 May 2021
Webinar aims
Show some caveats when using machine learning algorithms and give an insight what it means to use machine learning for statistical purposes.
Webinar learning outcomes
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Know how to identify problems with machine learning algorithms.
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Be aware of coverage and representativity of the population in the training set.
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Understand what is needed to validate a ML model.
Webinar content
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Correlation vs. Causation
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Annotations and the asymptotical behavior towards annotated data.
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Representativity of training sets
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Bias in classifications
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Explainable AI
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Concept Drift
Difficulty level
Introductory
Prerequisites for the webinar
None
Further reading and resources
Presentation material
Recording of the webinar