Machine Learning for Econometrics

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:

  • Bayesian inference;
  • Linear classification models;
  • Neural networks and deep learning;
  • Bagging and boosting;
  • Difference and similarities of methods in econometrics and machine learning (predictive versus causal inference).
  • Programming with Python
Slides Available soon

Teaching materials

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