Machine learning basics, part 1


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Workshop series
Computational and Data Systems Initiative




This workshop consists of two sessions: part 1 (14 April 2022) and part 2 (28 April 2022). Part 1 will introduce elementary concepts, such as learning problems, starting with the example of linear models. Part 2 will address more advanced concepts and models.

Are you interested in machine learning? If you are looking for a place to get started, then please join us for this workshop where we will cover basic concepts in machine learning theory and briefly survey some popular machine learning models.

At the end of this workshop (parts 1+2), you will be able to:
> Identify common machine learning problems and models.
> Understand basic concepts in machine learning theory and practice
> Create and run simple machine learning models using the scikit-learn Python library

Pre-requisites? Working knowledge of Python, linear algebra, calculus, and probability theory.

Date: Thursday April 14th, 2022
Time: 1PM to 3PM
Location: In person - Burnside Hall BH511
Instructor: Can Mekik, PhD candidate, Department of Cognitive Science, Rensselaer Polytechnic Institute.

This workshop is offered for free by the Faculty of Science to the McGill community. Due to the limited amount of spots available, if you sign up for a workshop and don't show up, you will not be allowed to attend another workshop this semester.
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