Date:
This workshop in on Saturday, September 22, 2018, 13:00 - 16:00h during the SMS Paris conference. Places are limited. Please pre-register by September 1 at:
https://www.strategicmanagement.net/paris/workshops/practical-machine-learning-workshop#/ Background:
Machine learning (ML) is rapidly changing society and research. Societally, ML increasingly influences the job interviews we get invited to, the products and services we get offered, the prices we need to pay, the political messages we see, and even the potential romantic partners we are introduced to. As for research, ML allows for the analysis of new data (more (e.g. "big" data) or different (e.g. text, images, voice, video) data, introduces new methods (e.g. LASSO, random forests, neural networks), influences new practices (e.g. systematic variable selection, hold-out samples for theory testing, combinations with existing econometric tools to strengthen casual inference (e.g. instrumental variable regression)), and will hopefully help find new answers to existing research questions as well as open up new research avenues.
Format:
The workshop is designed as an introduction to ML for scholars without ML experience. The focus of the workshop is on active learning. The workshop discusses three topics: regularization, natural language processing, and clustering. The structure for a given topic is as follows. First, an expert introduces a specific ML topic. Second, participants analyze data on their laptops. Data and scripts will be provided. During the computer lab, the experts and organizers will facilitate and provide practical assistance. Third, the expert concludes a topic by reflecting on the results.
Organizers:
Anoop Menon
Bart Vanneste
Facilitators:
Sen Chai
Anil Doshi
Andreas Schwab