Similar to: why do I always see my queen blunders after I made the move.

Since each model has only seen a portion of the data, we can assume it will give "honest" predictions. We can gather all of these predictions and give that to cleanlab which will analyze the probabilities and output a report of potentially mislabeled images.

docs.cleanlab.ai/stable/tutor...

I'm setting up K-fold cross validation producing K models, each trained on a subset of the training set and predicting on a validation set. Appending those predictions together, we ensure that the whole dataset has been seen but equally split amongst the models.

Because I want to spot issues in my training data, I can't use a model trained on that data to create predictions because it'll be too confident since it's seen the data before.

Victory!

I spawned two machines. Someone stops me.

It did not. Back to the drawing board.

If we find a fourth, we could even play 4-players chess or bughouse.

www.chess.com/terms/4-play...
www.chess.com/terms/bughou...

Making good progress. Here's a peek — Probably gonna take me another week or so.

It's tough because I'm also learning new things I may have not bothered learning in any other way given the potentially steep learning curve.