The term “machine learning model” refers to a mathematical framework trained on data to recognize patterns and make predictions. These models learn from historical data and improve their accuracy over time through processes like training and validation. Various types of machine learning models exist, including supervised, unsupervised, and reinforcement learning models, each suited for different applications, such as image recognition, natural language processing, or predictive analytics. The effectiveness of a model largely relies on the quality and relevance of the training data used.