Significance of training data

A machine-learning system consists of three main components. They are the training algorithm (e.g., neural network, decision trees, etc.), training data, and features. The training data is of paramount importance. The model learns directly from the data to create and refine its rules on a given task. Therefore, inadequate, inaccurate, or irrelevant data will render even the most performant algorithms useless. The quality and quantity of training data are a big factor in determining how far you can go in our machine learning optimization task.

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