Training data

Training data is the labeled or unlabeled information used to teach a machine learning model how to make predictions. It serves as the foundation for model training, helping the model recognize relationships between inputs and outputs.

Training data can be structured, semi-structured, or unstructured. However, it must be accurate, diverse, and representative of real-world conditions. The data can include text, images, audio, or numerical data, depending on the purpose of the model.

Developers often preprocess and clean training data to remove errors or biases. The better the training data, the more reliable and generalizable the system it’s used for will be in real-world applications.