Intro to Data Science Module 1: Introduction to Machine Learning (Session 2)

11:00 am to 12:00 noon PST | All sessions will be delivered live and online via the Gotowebinar system.

This webinar is part of the Introduction to Data Science Webinar Series

Practicum session

  • What is machine learning?
  • Supervised vs unsupervised learning
  • Model- and kernel-based methods
  • Measures of accuracy (test/train and cross-validation)
  • Causality and accuracy
  • Unsupervised learning as feature reduction

Watch recorded presentation below.
 

Presenter

Aman Verma Aman Verma  is a Data Engineer with a PhD in Epidemiology from McGill University, and an undergraduate degree in Computer Science. He has experience in developing machine learning systems with large databases, particularly for scientific data in healthcare. While he’s comfortable learning any programming language, he’s recently become particularly interested in R.

Aman is currently involved in a number of projects, including measuring how following opioid prescription guidelines can decrease the risk of opioid overdose, modelling trajectories of chronic obstructive pulmonary disease, and assessing how to best prioritize ambulance calls using secondary healthcare data.

 

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