本文从两个简单的经典非线性系统——双摆系统和罗斯勒系统入手，通过使用SINDy-PI算法对它们动力学方程的识别，展现了机器学习方法在处理非线性系统时的高效性与准确性，指出了该算法在数据驱动研究方面的优点. 并以此为契机，对计算物理课程中引入机器学习的有效路径进行了探索和讨论，研究结果可为计算物理课程的教学实践提供有益参考.

This paper begins by examining two simple classical nonlinear systems—the double pendulum system and the Rssler system. Through the use of the SINDyPI algorithm for identifying their dynamical equations, it demonstrates the efficiency and accuracy of machine learning methods in handling nonlinear systems and highlights the merits of this algorithm in datadriven approaches. Additionally, taking this as a basis, the study explores and discusses effective approaches to incorporating machine learning into the computational physics course. The findings provide valuable references for the practical implementation of teaching in computational physics.