[D] What is the best practice for adding new samples to the training set of a model once a new sample is discovered/acquired?

Web: https://www.reddit.com/r/MachineLearning/comments/uq281n/d_what_is_the_best_practice_for_adding_new/

Let’s say I have a trained model for which I used a training set T. If new samples become available, what is the best practice for using this new information to improve the model?
My thoughts are:
1) create a new training set T’ that contains the new samples and retrain the model
2) fine-tune the trained model by training a few epochs on only the new samples

Furthermore, if the new acquired samples are more important to the task …

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