Specifically, I would like to highlight some real-world examples that demonstrate just how powerful the MAP function is. It can be confusing, considering that you have to use it with LAMBDA functions.

Row precision vs. Aggregation errors: MAP is the best way to use "greedy" functions like AND or OR in a single, dynamic ...

Abstract: The current mainstream time series prediction methods exhibit commendable accuracy in prediction, but they often lack interpretability. One approach to address this issue is through the ...

Abstract: Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. However, advanced methods like CutMix blend images and assign labels ...