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ECON 434

MACHINE LEARNING AND ALGORITHMS FOR COMPUTATIONAL ECONOMICS

Credit Hours: 4 · Undergraduate Upper-Level

This course will cover supervised learning (both regression and classification) , reinforcement learning, and model selection via validation procedures. The course prepares students to apply a variety of classical and cutting-edge machine learning techniques to problems in economics. Students will be taught principled approaches that adhere to best practices and promote understanding and transparency. Graduate/Undergraduate Equivalency: ECON 634 . Mutually Exclusive: Cannot register for ECON 434 if student has credit for ECON 634 .

Prerequisites & course information

Short Title: MACHINE LEARNING FOR COMP ECON Department: Economics Grade Mode: Standard Letter Course Type: Lecture/Laboratory Credit Hours: 4 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): ECON 208 and ECON 308

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