Are there (complex) tabular datasets where deep neural networks (e.g. more than 3 layers) outperform traditional methods such as XGBoost by a large margin?
I'd prefer tabular datasets rather than image datasets, since most image dataset are either too simple that even XGBoost can perform well (e.g. MNIST), or too difficult for XGBoost that its performance is too low (e.g. almost any dataset that is more complex than CIFAR10; please correct me if I'm wrong).