Training Variables

Training variables are the different factors that influence how a machine learning model learns from data. These include aspects like the speed at which the model updates its knowledge (learning rate), the size of the data batches it processes at once (batch size), how many times it goes through the entire dataset (epochs), and the way it adjusts its internal parameters to improve accuracy (optimizer). Tuning these variables helps optimize the model's performance, ensuring it learns effectively without overfitting or underfitting the data.