Machine Learning and R
Foundation of Machine Learning for Prediction and Causal Inference in R, 3-Day Remote Workshop Taught by Towhid Islam, 14-16 Jul 2022
POSTING TYPE: Revisits
Author: Towhid Islam
FOUNDATION OF MACHINE LEARNING FOR PREDICTION AND CAUSAL INFERENCE IN R
A 3-Day Remote Workshop Taught by Towhid Islam, PhD., University Research Leadership Chair and Professor, Department of Marketing and Consumer Studies, University of Guelph, Canada.
This workshop is designed for academics, students, and professionals interested in the foundation of machine learning procedures (MLPs) such as regularization, multivariate adaptive splines, random forest, gradient boosting, neural network, and super learner. Workshop will introduce potential outcome framework of causal inferences and cover recent advances in causal inference procedures using MLPs, including augmented inverse probability weights (AIPW), targeted maximum likelihood estimation (TMLE), double machine learning, and causal random forest.
Thursday, July 14, 2022 – Saturday, July 16, 2022.
Live Lecture and Lab Session, 10 am–2:30 pm EST (New York Time) each day with 30 minutes break at noon. Video-recorded versions will be made available after each session.
Payment: The fee of Canadian $700 Regular, $500 for Students, includes lecture material, R codes, and data.
Visit the link for details: https://dataorbit.ca/course/12