Year: 2024
Type: conference-paper
Abstract: This paper discusses the application of machine learning in graduate education in finance, emphasizing its importance in data analysis, prediction, and causal inference. The paper points out that machine learning can enhance students' professional competence, expand their knowledge areas, and enhance their work abilities. Through theoretical teaching and research applications, machine learning methods can help process large amounts of unstructured data and combine with traditional econometric methods to improve the accuracy and explanatory power of research. The survey results support the effectiveness of machine learning teaching. At the end of the paper, it is proposed to continuously update the teaching content of machine learning technology, while paying attention to its limitations, in order to promote the improvement of students' comprehensive abilities.
Authors: Kan Zhang, Fengqingyang Wang, Suze Wang
Institutions: Zhongnan University of Economics and Law, Xiamen University
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4409965758