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Do You Want Big Data or Small Data?
A lot of a time, when you're training on several millions of rows, several million data points, the vast majority of them are actually not moving the needle that much for a model. There is a higher likelihood that a much larger sample will yield the right diverse like properties that you'd want in your data set for your model to generalize well. But depending on which direct you go with that fork, you might end up with different techniques. I'll throw two examples out there, like active learning is a very good technique for the sub selection and nsorto like iteration on very small data sets while something like week supervision may be better at larger scale labelling sort of tasks.