Parameters

Parameters are the underlying settings or variables within a machine learning model that influence its behavior. Think of them as the "knobs" the model adjusts during training to better understand and make predictions from data. For example, in a neural network, parameters determine how input information is processed to produce outputs. Fine-tuning these parameters allows the model to improve accuracy. Essentially, they are the internal values that the model learns to capture patterns and relationships within the data, enabling it to perform tasks such as recognizing images or understanding language more effectively.