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Guest lecture with a renowned expert

As part of the framework of the Mu­nich Grad­uate School in Eco­nom­ics (MGSE) guest lec­ture pro­gram, the in-ter­na­tional­ly re­nowned expert Prof. Dr. Ste­phen Han­sen (Uni­versi­ty of Ox­ford) held a lec­ture on the latest de­velopments and im­ple­men­ta­tions of ma­chine learn­ing in the field of eco­nom­ics. The lec­ture “Ma­chine Learning Methods for Econ­omists“ was tai­lored for ad­vanced stu­dents of the Elite Grad­uate Pro­gram “Mas­ter in Quan­tita­tive Eco­nom­ics“ to give them an in­sight into the latest tech­niques and their appli­cati­ons.

Large data sets require new analytical methods

The availability of large data sets with millions of data points and a large number of attributes brings new opportunities for innovative methods of empirical assessment. The term “machine learning” refers to the methodical statistical analysis of large data sets, which enable scientists to detect complex interrelations. Texts can also be analyzed and processed by machine learning.

In his lecture, Prof. Dr. Stephen Hansen gave a comprehensive overview of methods and implementations to MGSE master and PhD students. He covered both the topic of “unsupervised learning” and “supervised learning”. 

This guest lecture successfully enabled the students of the Elite Graduate Program "Master in Quantitative Economics" to handle high-dimensional or unstructured data with proficiency and to apply machine learning in their innovative research.

Text: Elite Graduate Program "Master in Quantitative Economics“