A pre-trained machine learning (ML) model has already been trained on a large dataset for a specific task. It has learned extensively from this data, so you don’t have to start from scratch when you use it. These models are often used as a foundation for developing new ML models because they come with initial weights and biases that can be fine-tuned for similar tasks. This means you only need to teach the model the specific things you need, allowing it to help you much faster and more efficiently.
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