Probabilistic ML - Lecture 1 - Introduction
Автор: Tübingen Machine Learning
Загружено: 2020-04-17
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This is the first lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig in the Summer Term 2020 at the University of Tübingen.
Time-stamped slides available at https://uni-tuebingen.de/en/180804.
Contents:
Introduction to uncertain reasoning
Kolmogorov's axioms and basic rules of probabilistic reasoning
Example uses of Bayes' Theorem
Slides 4 & 13 (deductive v probabilistic reasoning) are based on prior material developed by Stefan Harmeling for a lecture course held jointly with Philipp Hennig in 2012/2013.
© Philipp Hennig / University of Tübingen, 2020 CC BY-NC-SA 3.0
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