Slow warm start is a technique used to gradually increase the learning rate of a machine learning model during training. This allows the model to converge more smoothly and can help prevent issues such as overfitting or poor performance. Slow warm start can be implemented by starting with a small learning rate and gradually increasing...
Slow cold start refers to the longer initialization time required for a machine learning model when it is first deployed or when it is being used after a long period of inactivity. This can happen when the model is very large or when it requires a significant amount of data to be loaded before it...
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