Loss Function

A loss function is a mathematical tool used to measure how well a model predicts outcomes compared to actual results. Think of it as a scorecard: it quantifies the difference between what the model predicted and what actually happened. A lower score indicates better performance, while a higher score suggests the model needs improvement. In essence, it helps developers adjust and refine algorithms to enhance accuracy, ensuring that predictions align more closely with real-world data. By minimizing the loss, we strive for better decision-making and outcomes in applications like finance, healthcare, and more.