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1

One option is fingerprinting. If two objects have the same fingerprint, they are probably the same object. Depending the technique used, the fingerprint can not tell about approximate duplicates.


2

The reasoning will be: "The more data for training the better". Then you have to keep in mind that the validation/hold-out set has to resemble how it should work on production/testing. The theory is that the larger the training data, the better the model should generalize. The validation set can be much smaller, on extremely big dataset you can ...


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