Material for my one-day tutorial at ESOBE2017
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README.md

README.md

Machine Learning Models and Methods for Econometricians

by Mattias Villani, Division of Statistics and Machine Learning, Linköping University


09.00-09.15 Coffee/Tea

09.15-10.00 Gaussian Process Regression

Reading:

Software:

Code snippets:

  • R code for simulating from a GP.

Extras:


10.00-10.15 Break

10.15-11.00 Gaussian Process Classification and Optimization

Reading:

Software:

11.00-11.15 Coffee/Tea break

11.15-12.00 Distributed and Subsampling MCMC

Reading:


12.00-13.15 Lunch

13.15-14.00 Text as data - Topic Models

Reading:

Software:


14.00-14.15 Break

14.15-15.00 Variational Bayes

Reading:

Software:

Edward for variational inference - a probabilistic programming language (think Stan)


15.00-15.15 Coffee/Tea break

15.15-16.00 Deep Learning

Reading:

Software:

Code for analyzing the Bank Marketing Data from the UCI repository: