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Expand Up @@ -25,6 +25,16 @@ This course will present the basic building blocks of these models, the techniqu

## Discussion Board: <https://probml-forum.jessebett.com/>

## Lectures and Tutorials ([GoogleDrive](https://drive.google.com/drive/folders/1ohy7FHmgQNFIp3IHsIz2T4AWnvrKOVF9))
* [Lecture 1 Notes](lec1.md) and [blackboard](https://drive.google.com/file/d/1bNeQn0EOF-2UGPP76hjgsn_I0KZKd0yM/view?usp=sharing) and [zoom recording](https://www.youtube.com/watch?v=6H4STM7mvuk&list=PLHOaL7udqbt9WQBFtkg9AEaxZe2ddXpXJ&index=1)


* [Tutorial 1 Code](/Tutorial%201) and [zoom recording](https://www.youtube.com/watch?v=nNGlPossbNM&list=PLHOaL7udqbt9WQBFtkg9AEaxZe2ddXpXJ&index=2)


* [Lecture 2 Notes: Probabilistic Reasoning](lec2.md) and [blackboard](https://drive.google.com/file/d/168FckF00dwUT_B1rkCvport3DVRTTUOm/view?usp=sharing) and [zoom recording](https://mymedia.library.utoronto.ca/play/6e481bc25acb844a11a7ba01ad1c9111)

* [Tutorial 2 Slides](https://drive.google.com/file/d/1vnIRx3RAwIhwi29WYTcj0QfOKZ_Ha7ZN/view?usp=sharing) and [zoom recording](https://play.library.utoronto.ca/play/236a033286fcd656f7cc08055f7fd164)

## Teaching Team

Expand Down Expand Up @@ -193,15 +203,3 @@ There is no required textbook for this class. Readings from various sources will
- David MacKay (2003) *Information Theory, Inference, and Learning Algorithms* <http://www.inference.phy.cam.ac.uk/mackay/itila/> .
- Kevin Murphy (2012) *Machine Learning: A Probabilistic Perspective*.


# Lecture Notes


## [Lecture 1](lec1.md)


## [Tutorial 1](tut1.md)


## [Lecture 2: Probabilistic Reasoning](lec2.md)