👉 The Lots Fluid, often referred to as the "Loss Function" in machine learning contexts, is a mathematical representation used to quantify the discrepancy between a model's predictions and actual outcomes. It serves as a guide for optimizing the model's parameters during training, helping to minimize errors and improve accuracy. This fluid is central to various loss functions like Mean Squared Error (MSE) for regression tasks or Cross-Entropy Loss for classification tasks, each tailored to specific problem types. By adjusting the model based on feedback from this function, it effectively learns to make better predictions over time.
