Machine Learning and R
Foundation of Machine Learning for Prediction and Causal Inference in R, Remote Workshop Taught by Towhid Islam, 24-26 Nov 2022
Author: Towhidul Islam
Foundation of Machine Learning for Prediction and Causal Inference in R
A 3-Day Remote Workshop Taught by Towhid Islam, PhD., Professor, Department of Marketing and Consumer Studies, University of Guelph, Ontario, 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 causal inferences with potential outcome framework and cover recent advances using individual MLPs and doubly robust approaches with super learners such as augmented inverse probability weights (AIPW), targeted maximum likelihood estimation (TMLE), and double machine learning approaches such as causal random forest.
Thursday, November 24, 2022 – Saturday, November 26, 2022.
Live Lecture and Lab Session: 10 am–3:00 pm Eastern Time (New York Time) each day with one hour break at noon. Video-recorded versions will be accessible for 8 weeks,
Payment: The fee of Canadian $700 Regular, $500 for Students, includes lecture material, R codes, and data.
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