Model Training

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Model training is the stage where a machine learning model learns from examples. It’s given training data and adjusts itself so it can make better predictions on similar inputs later. For instance, if a model sees many labeled images of cats and dogs, it can learn the patterns that separate the two and apply that knowledge to new images it has not seen before.

This process usually involves tweaking the model’s internal parameters until it gets better at performing its task. The more accurate the training data and the better the model’s design, the more effective the model will be at making correct predictions on new data.

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