Research Portal on Machine Learning for Social and Health Policies

09/25/2021

We are presenting on October 20.

Prof. Yigit Aydede, Saint Mary's University, Halifax, Canada

10/23/2020

We are at BigSurv20 (https://www.bigsurv20.org)

We are presenting our first results from "What can be predicted from a national health survey? Is cancer one of them?" (https://www.bigsurv20.org/programme?sess=28 #23)

Welcome to BigSurv20 Big Data Challengeregistration is open! Newsletter BigSurv20 will be VIRTUALLY every Friday this November and early December: We've got great news for you! BigSurv20 will take place online this year. Registration: Attendance of all BigSurv20 conference events is free of charge,....

08/06/2020

https://sobeyschoolprosperitynetwork.com/upcoming-events/what-machine-learning-can-tell-us-about-the-post-pandemic-labour-market-webinar

07/26/2020

We completed our 3-day Summer School followed by 2-day Webinar with 10 panelists on Friday. Webinar presentations will be available offline at our website soon.

Summers school lectures and lecture materials will also be available (with a small fee).

Please check out our website next month to access both events.

We thank all panelists and attendees. It was a great event!

06/22/2020

https://smu.ca/academics/sobey/sobeyeventslisting/machine-learning-summer-school.html

Machine learning is programming computers to build predictive models for making inference from samples for accurate out-of-sample predictions and decisions. As an applied economist, or researcher in a related field, if you feel that you need to learn these contemporary machine learning methods, impl...

06/22/2020

https://www.dal.ca/faculty/science/economics/news-events/news/2020/06/18/machine_learning_for_economists_and_applied_social_scientists.html

Online Lectures (with fee) and Webinar Series (free) have been organised by Leading Researchers on Machine Learning designed for Academic Economists and Social Scientist between July 20-24, 2020. Lectures and webinars' main target group is Academic Economists who want to start learning ML methods.