Hey everyone! 👋
So, I’ve been diving into this whole "how to split dataset into batches" thing, and honestly, it’s kinda tricky to get it *just right*. Like, do you go for equal-sized batches every time? Or mix it up depending on the data?
I’ve found that shuffling the data first helps a ton—keeps things random and avoids bias. But then, when you’re figuring out how to split dataset into batches, size matters too. Too big, and your GPU cries. Too small, and training takes forever.
Also, anyone else struggle with imbalanced datasets? I’ve been experimenting with stratified sampling, and it’s been a game-changer.
What’s your go-to method for how to split dataset into batches? Any hot tips or horror stories? Let’s hear it! 🚀
So, I’ve been diving into this whole "how to split dataset into batches" thing, and honestly, it’s kinda tricky to get it *just right*. Like, do you go for equal-sized batches every time? Or mix it up depending on the data?
I’ve found that shuffling the data first helps a ton—keeps things random and avoids bias. But then, when you’re figuring out how to split dataset into batches, size matters too. Too big, and your GPU cries. Too small, and training takes forever.
Also, anyone else struggle with imbalanced datasets? I’ve been experimenting with stratified sampling, and it’s been a game-changer.
What’s your go-to method for how to split dataset into batches? Any hot tips or horror stories? Let’s hear it! 🚀