INF2D: 22: Introduction to Bayesian Networks
This folder provides an introduction to Bayesian Networks, which is a compact way of representing a joint probability distribution. In later sections, we'll see that Bayesian Networks are useful for providing a practical approach to probabilistic inference.
Lecture Slides
Lecture Slides (Last Year's Notes Version)
Required Reading
R&N Section 14.1–14.3 or NIE Chapter (14) "Probabilistic Reasoning", Sections 1–3.
NOTE: The abbreviation R&N refers to:
“Artificial Intelligence: A Modern Approach” Third Edition, Russell R & Norvig P, Prentice Hall, 2010 (R&N).
The abbreviation NIE stands for the following edition of the same book:
“Artificial Intelligence: A Modern Approach” Third Edition, Pearson New International Edition, Russell R & Norvig P, Pearson, 2014.
Quiz 23: Probabilistic Reasoning with Bayesian Networks
These questions are designed to test your understanding of the above course content; doing this quiz does not contribute to your overall grade. Some questions require a text answer. You can ask for formative feedback on these from your tutor or on piazza. Other questions are multiple choice or they require a numeric answer: you will get immediate feedback for these. Please don't attempt this quiz until you have acquainted yourself with this lecture and the required reading.
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