Deep Learning in Economics and Finance
Fei Tan (econdojo@gmail.com)
Department of Economics, Chaifetz School of Business, Saint Louis University
Embedded Files
Co-hosted by
Date: May 31 and June 1, 2025, 10:00 am~12:00 pm Eastern Time
Location: Virtual - Zoom, Registration required
Course Description
Course Description
Artificial intelligence should be made accessible to all. To this end, we provide a spelled-out introduction to neural networks and their applications for students from all disciplines, regardless of their background or area of study. Starting with the classical problem of image recognition, students will delve into the intricacies of modeling multilayer perceptrons, backpropagation algorithm for optimization, model training and evaluation, as well as extensions and variants of the basic architecture. By empowering students with hands-on modeling and programming skills, we aim to democratize AI technology and foster a community of `AI ninjas' capable of harnessing its transformative potential for innovation, economic growth, and the betterment of humanity. Topics covered include:
Donation
Donation
IMIM is a non-profit organization, and this mini-course is offered free of charge thanks to generous sponsorship from the McCoy College of Business of Texas State University. If you would like to support IMIM and help us continue providing accessible educational content, you can make a donation using the link below. Every contribution, big or small, makes a difference.
IMIM is a non-profit organization, and this mini-course is offered free of charge thanks to generous sponsorship from the McCoy College of Business of Texas State University. If you would like to support IMIM and help us continue providing accessible educational content, you can make a donation using the link below. Every contribution, big or small, makes a difference.
Thank you for your support!
Preparing for the Mini Course
Preparing for the Mini Course
Sign-up for GitHub (required) 👉
GitHub classroom invitation: https://classroom.github.com/a/lRWY17AH
Instructor
Grounded in first principles, Dr. Fei Tan's research agenda is organized around three areas: macroeconomics, Bayesian statistics, and game theory. One line of his research develops time and frequency-domain approaches to dynamic equilibrium models of expectations formation. Another line develops Markov chain Monte Carlo methods for estimating large-scale structural models. These tools are applied to study monetary and fiscal policy, asset prices, and social networks. Recently, he likes to train neural nets regularized by economic theory. His previous research studies the evolution of cooperative and altruistic human behavior.
As an educator, Dr. Tan teaches economics, statistics, and computer science to both high school and college students. He also co-founded “Business School 101”, a rapidly growing YouTube channel dedicated to providing practical business education to a broad audience. Beyond the classroom, he is a thematic investor for space economy and has rich experience in derivative trading.
Dr. Tan earned his B.A. in Economics from Zhejiang University, both M.A. in Mathematics and Ph.D. in Economics from Indiana University, and joined Chaifetz School of Business currently as Associate Professor of Economics at Saint Louis University.
Organization Committee:IMIM:Ren Zhang Shuwei ZhangFei TanRuizhi DongTexas State University:Emmanuel AlanisYao-Yu ChihRen Zhang
Page updated
Google Sites
Report abuse