How to Efficiently Handle Splitting into Batches in Sklearn for Large Datasets?

Hey folks!

So, I’ve been working with some *massive* datasets lately, and I’m trying to figure out the best way to handle splitting into batches sklearn. Like, my data is so big that my laptop just gives up halfway through. 😅

Anyone got tips on how to do this efficiently? I’ve tried using `train_test_split`, but it’s not cutting it for these sizes. Should I be looking into `KFold` or maybe something like `BatchGenerator`?

Also, is there a way to avoid loading the entire dataset into memory at once? Cuz that’s kinda killing my workflow.

Thanks in advance! 🙌