Deep Learning is heavily used in Kaggle competitions when there is image data.
Even in non-image data competitions, a deep neural network will often be one of the models chosen to ensemble. They generally perform slightly worse than XGBoost models, but have the advantage that they often aren't closey correlated, which helps fighting overfitting when tuning ensembling hyperparamters.
Even in non-image data competitions, a deep neural network will often be one of the models chosen to ensemble. They generally perform slightly worse than XGBoost models, but have the advantage that they often aren't closey correlated, which helps fighting overfitting when tuning ensembling hyperparamters.