Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. In this hands-on introductory workshop, you will learn how to apply Machine Learning, and get familiar with the basics of Deep Learning. MATLAB provides an environment to apply advanced techniques without requiring extensive coding nor experience in machine learning.

• Learn the fundamentals of machine learning  (supervised learning, feature extraction, and hyperparameter tuning)
• Explore pre-processing and powerful visualization techniques
• Build and evaluate machine learning models for classification and regression of various data formats (signals, images, text)
• Perform hyperparameter tuning and feature selection to optimize model performance
• Discuss interoperability with other platforms
• Learn how to deploy Machine Learning models

Level: Intermediate

Length: 3 Hours

Format: Lecture + Hands-on

Prerequisites: Working knowledge of MATLAB

:: Fri. June 14 ::

09:00 to 12:00 

Registration link

Compute Ontario Summer School is a series of online courses on Advanced Research Computing, High Performance Computing, Research Data Management, and Research Software. It runs from June 3 to June 21, 2024. The courses are delivered each workday from 9:00am to 4:30pm (EDT) with a lunch break,  in two parallel streams. Pick-and-choose the course(s) you want to attend. Registration is free. Please register early as  courses have a limited capacity. The Summer School is jointly delivered by SHARCNET, SciNet, Centre for Advanced Computing, in collaboration with the Alliance and RDM experts from across Ontario and Canada.