Training Data
Training data is a set of data used to train a machine learning model. It is a subset of the overall dataset and is used to teach the model how to make predictions by adjusting its internal parameters. The quality and quantity of the training data are crucial to the success of the model. The data should be representative of the problem domain and cover a wide range of scenarios. It should also be labeled correctly, meaning that each data point should have a corresponding label or output that the model is trying to predict. The process of selecting and preparing the training data is known as data preprocessing, which involves cleaning, transforming, and normalizing the data to make it suitable for the model.
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