Machine Learning for Econometrics
This course will be a mix of machine learning theory in regular lectures and application of this knowledge on large datasets in practical sessions.
- 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
- C.M. Bishop (2006). Pattern Recognition and Machine Learning.
- Other course materials will be made available on Canvas