Sure, here’s a simple explanation: A model typically runs on data using algorithms that help it learn patterns and relationships within the data. Common algorithms include linear regression, decision trees, random forests, support vector machines, neural networks, and clustering algorithms like k-means. Each algorithm has its strengths and weaknesses, making them suitable for different types of data and tasks.