Coordinator:
Juri Marcucci, Bank of Italy
Lecturers
Arthur Charpentier (UQAM, Canada)
Emmanuel Flachaire (AMSE, France)
THIS COURSE IS FULLY BOOKED
Course description:
Do you feel lost in the random forests? Do you need some career boosting? Would you like to demystify magic words like cross-validation, bagging, shrinkage, etc? Or discover what is hidden behind wild acronyms like GAM, LASSO, GBM, etc. that you heard during that meeting or at the coffee machine or at that seminar with a fancy title? If so then you should consider attending this one-week intensive course on machine learning techniques.
These lectures has been conceived by econometricians for econometricians. The sessions proceed step by step, recalling the fundamental statistical concepts at the heart of the modern learning techniques. Their relative merits are illustrated by means of several case studies with real data.
Course Schedule:
Monday July 15
Session 1A (Flachaire): Introduction, Model Misspecification, Nonlinearities, Nonparametric Econometrics (kernels, splines and GAMs)
Session 1B (Charpentier): Loss Functions, Objective Functions and Penalty (quantile regression, LASSO, ridge)
Tuesday July 16
Session 2A (Flachaire): Cross Validation, Overfit, Bootstrap and Bagging)
Session 2B (Flchaire): Classification, part I: logistic regression, trees, forests
Wednesday July 17
Session 3A (Charpentier): Classification, part II: neural networks and deep learning, and Model Selection (ROC, AUC))
Session 3B: excursion
Thursday July 18
Session 4A (Charpentier & Flachaire): Group “Hands-On Classification” on Real Data)
Session 4B (Flachaire): Regression: boosting, regression trees and forests
Friday July 19
Session 5A (Charpentier & Flachaire): Group “Hands-On Regression” on Real Data)
Session 5B (Charpentier): Algorithmic and Optimization Issues, Extension of Machine Learning Techniques to Time Series
Saturday July 20
Session 6A (Charpentier): Causality with Machine Learning Algorithms)
Contacts
For more information: Antonella Mallus e-mail: info@side-iea.it
For administrative issues : Alessandra Picariello phone:+39 0512092637; e-mail: alessandra.picariello@unibo.it