Objectives function

An objectives function, often called a "loss function," is a formula used in machine learning to measure how well a model is performing. It quantifies the difference between the model's predictions and the actual correct answers. The goal is to minimize this value, meaning the model's guesses are getting closer to the true data. Think of it as a score that tells you how well the model is doing; lower scores indicate better performance. By consistently optimizing this function during training, the model learns to make more accurate predictions.