Course 493: Intelligent Data Analysis and Probabilistic Inference

**Notices:**

Course Outline

Lecture 1 (notes:slides) Bayes' Theorem and Bayesian Inference

Lecture 2 (notes:slides) Bayesian Decision Trees

Lecture 3 (notes:slides) Evidence and message passing

Lecture 4 (notes:slides) Inference in singly connected networks

Lecture 5 (notes:slides) Building networks from data

Lecture 6 (notes:slides) Cause and Independence

Lecture 7 (notes:slides) Model Accuracy

Lecture 8 (notes:slides) Approximate Inference

Lecture 9 (notes:slides) Exact Inference

Lecture 10 (notes:slides) Probability propagation in Join Treess

Lecture 11 (slides) Graphical Models

Lecture Slides on Gaussian Processes

Lecture Slides on Bayesian Optimisation

Coursework: Data Files for the coursework

Errata

Past Exam Papers:

2011 , 2012 , 2013 , 2014 , 2015 , 2016

2017

Lecture 1 (notes:slides) Bayes' Theorem and Bayesian Inference

Lecture 2 (notes:slides) Bayesian Decision Trees

Lecture 3 (notes:slides) Evidence and message passing

Lecture 4 (notes:slides) Inference in singly connected networks

Lecture 5 (notes:slides) Building networks from data

Lecture 6 (notes:slides) Cause and Independence

Lecture 7 (notes:slides) Model Accuracy

Lecture 8 (notes:slides) Approximate Inference

Lecture 9 (notes:slides) Exact Inference

Lecture 10 (notes:slides) Probability propagation in Join Treess

Lecture 11 (slides) Graphical Models

Lecture Slides on Gaussian Processes

Lecture Slides on Bayesian Optimisation

Coursework: Data Files for the coursework

Errata

Past Exam Papers:

Note that for the topics covered in lectures 11-17 the exam questions may be different in style from earlier years.

2005 , 2006 , 2007 , 2008 , 2009 , 20102011 , 2012 , 2013 , 2014 , 2015 , 2016

2017

Tutorial 1 (problems
:solutions )
Lamda and Pi messages

Tutorial 2 (problems :solutions) Causal Networks & Multiple Parents

Tutorial 3 (problems : solutions) Multiply connected networks

Tutorial 4 (problems :solutions) Model Accuracy

Tutorial 5 (problems :solutions) Join Trees

Tutorial 6 (problems :solutions) Graphical Models

Useful Links

Notes on Linear Algebra

Notes from the Mathematics for Inference and Machine Learning Course

Bishop: Chapter on Graphical Models

Tutorial 2 (problems :solutions) Causal Networks & Multiple Parents

Tutorial 3 (problems : solutions) Multiply connected networks

Tutorial 4 (problems :solutions) Model Accuracy

Tutorial 5 (problems :solutions) Join Trees

Tutorial 6 (problems :solutions) Graphical Models

Useful Links

Notes on Linear Algebra

Notes from the Mathematics for Inference and Machine Learning Course

Bishop: Chapter on Graphical Models