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Graduate Programs

ECO4051H1S Special Topics: Machine learning and data mining

Many important economic questions remain unanswered, partly because the data necessary to address them is encoded into high-dimensional data structures such as text or images. Applied economists have become increasingly interested in using machine learning models to transform these data into simpler representations, which can be used as inputs for subsequent economic analysis. After introducing statistical learning, this course provides a comprehensive understanding of some of the most capable supervised learning models including random forest, gradient boosted trees, or neural network architectures to make sense of these complex forms of data and perform original economic analysis. From a strong base in theory and mathematical formalisation, focus is kept on intuition and effective implementation using Python.

Section L0101, Winter 2022–23

Instructor: Clement Gorin
Day/time: W11-2

Delivery Method & Instructions: In Person

Location: SS 1087
TA: Saba Ale Ebrahim