Introduction to Machine Learning modelling techniques

Machine Learning (ML) is becoming an increasingly important part of information systems development in various disciplines. Techniques based on machine learning have been applied successfully in diverse fields ranging from pattern recognition, computer vision, spacecraft engineering, finance, entertainment, and computational biology to biomedical and medical applications. In this iSkills workshop, we’ll discuss an overview of common ML modelling techniques as well as strategies on applying such techniques to common industry problems. Specifically, we’ll consider:

• Differences between supervised, semi-supervised, and unsupervised learning
• Comparing transductive and inductive learning
• Categorizing ML modeling techniques (e.g. clustering, classification, regression, etc.)

By the end of this workshop, you’ll be able to:

• Understand basic ML modelling techniques
• Apply ML modelling techniques in common use cases as seen in industry problems

Instructor: Rohith Sothilingham, Senior Cloud Architect, Deloitte, and PhD student, Faculty of Information

Date and Time: October 13, 2022 from 6-8 pm

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