To effectively engage with this article, it is recommended that the reader has a foundational knowledge of Python, including familiarity with the prevalent nonadiabatic dynamics package Newton-X. Additionally, an understanding of NAMD principles is beneficial, as our discussions incorporate NAMD data. A basic understanding of fundamental machine learning concepts, such as evaluation metrics and data partitioning strategies, is assumed to grasp the more advanced topics discussed in this paper on unsupervised learning.