UofT Data Science Workshop: Intro to Classification with R

May 4, 2017 @ 6:00 pm – 9:00 pm
Department of Computer Science Innovation Lab at U of T
2nd Floor
Sigmund Samuel Library Building 9 King's College Circle, Toronto

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This meetup is only for students at the University of Toronto. Due to space constraints, we can only accept 90 students in the room on a first-come, first-serve basis.

In the meetup, we will cover popular classification algorithms including:

– k-Nearest Neighbors

– Logistic Regression

We will study how these classification methods work, some of their benefits and drawbacks. We will then apply these methods to real data sets using R during a hands-on session. This lecture is half lecture and half hands-on.


Please bring your laptops to take part in the hands-on session. Please sign up for an account on https://datascience.ibm.com before the event.

Meetup is limited to 120 attendees, to optimize the experience of the attendees.

Livestream will be available on a best-effort basis.

University of Toronto students:

This workshop is for UofT students, to provide skills and training for two upcoming hackathons sponsored by IBM Big Data U:

1) ASA DataFest 2017 – May 5 to 7, 2017

DataFest is sponsored by the American Statistical Association (https://www.amstat.org/education/datafest/).  The event is like a hackathon, for undergraduate students, except the problem is a data analysis problem, rather than a programming problem.  Teams of students get a dataset on Friday afternoon and work on the problem until Sunday afternoon where they present their results.  After two days of intense data wrangling, analysis, and presentation design, each team is allowed a few minutes and no more than two slides to impress a panel of judges.

2) Stem Fellowship Big Data Challenge 2017 – May 1 to 30, 2017

The BDC, in association with IBM Big Data University, will take place in the month of May, with the morning and afternoon of May 1st marking the BDC’s Orientation Day. The remainder of the month will involve teams working independently on their projects at their own respective paces; participants will also be invited to ongoing workshops for data science tools over the course of the competition, as well as talks from leaders in industry and academia.


Joseph Santarcangelo, Ph.D. (Data Scientist, IBM)

Saeed Aghabozorgi, Ph.D. (Sr. Data Scientist, IBM)