《机器学习》课程思政教学研究——以最大熵模型为例

Research on Ideological and Political Teaching of “Machine Learning” Course—Taking the Maximum Entropy Model as an Example

摘要: 《机器学习》是面向统计学本科生开设的核心课程，旨在培养学生在掌握统计学习理论与方法的同时能够具备将数学模型应用于实际问题的能力。课程中蕴含丰富的思政元素，如公平决策、科学精神与信息伦理等。本文以“最大熵模型”为例，探讨其在课程思政教学中的设计，通过融合数学模型与价值观教育，引导学生树立客观、公平、辩证的科学观，提升其社会责任感与专业使命感。

Abstract: “Machine Learning” is a core course offered to undergraduate students majoring in statistics, aiming to cultivate students’ ability to apply mathematical models to practical problems while mastering the theories and methods of statistical learning. The course is rich in ideological and political elements, such as fair decision-making, scientific spirit and information ethics. This article takes the “maximum entropy model” as an example to explore its design in ideological and political education in courses. By integrating mathematical models with value education, it guides students to establish an objective, fair and dialectical scientific view, and enhances their sense of social responsibility and professional mission.