Training

Training refers to the process of teaching a machine learning model to recognize patterns and make predictions by exposing it to a dataset. During training, the model learns from the data by adjusting its internal parameters to minimize errors between its predictions and the actual outcomes. This process involves iteratively feeding the model with input data, comparing its outputs to the correct answers, and refining its predictions through techniques like gradient descent. The goal is to enable the model to generalize well so that it can make accurate predictions on new, unseen data.