Training Data

Training data is a collection of examples used to teach machine learning models how to perform specific tasks, consisting of input samples and their corresponding desired outputs.

Training data forms the foundation upon which machine learning models learn patterns and relationships. The quality and quantity of training data directly impacts how well a model can generalise to new, unseen examples and perform its intended task effectively.

The process of using training data involves feeding it through the model repeatedly, allowing the model to adjust its internal parameters to better map inputs to desired outputs. This iterative process, known as training, continues until the model achieves satisfactory performance on both the training data and separate validation data.

Examples

• Labelled images for computer vision
• Text conversations for chatbots
• Historical stock prices for financial forecasting
• Medical records for disease diagnosis
• Audio recordings for speech recognition