Machine Learning for Economists (ECO-AD-MACHLEAR)


Department ECO
Course category ECO Advanced courses
Course type Course
Academic year 2021-2022
Term BLOCK 1
Credits 1 (EUI Economics Department)
  • Prof. Sergio Pastorello (University of Bologna)
Contact Simonsen, Sarah


 A 20 hour course in Machine Learning tools for economists. At the end of the course the student will have a good understanding of the main tools used in machine learning. In particular, he/she: - understands and knows how to apply key aspects of machine and
statistical learning, such as out-of-sample cross-validation, regularization and scalability - is familiar with the concepts of supervised learning, regression and classification - understands and can apply the main learning tools such as lasso and ridge regression, regression trees, boosting, bagging and random forests, support vector machines and neural nets. - The course will put special emphasis on empirical applications using the R software.

Problem sets (30%) and a final project (70%).


see under Goals

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Page last updated on 21 September 2018

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