Machine Learning for Econometrics #

Coure Description on UvA’s website

Topics #

This course will be a mix of machine learning theory in regular lectures and application of this knowledge on large datasets in practical sessions.

Topics include:

• nonlinear regression;
• neural networks and deep learning;
• boosting, bagging and random forest;
• machine learning methods for causal inference (e.g., causal forest, double-lasso, debaised-ML)

Teaching materials #

• Online reader MachineLearningTheory.org
• C.M. Bishop (2006). Pattern Recognition and Machine Learning.
• Other course materials will be made available on Canvas