The training of deep learning models, particularly those involving CNNs and GRUs, requires significant computational resources. High-performance GPUs (Graphics Processing Units) were used to accelerate the training process, allowing for faster computation of the large number of parameters involved in the models. A multi-GPU setup may be considered for larger datasets to further enhance training efficiency. Sufficient RAM and storage capacity are also essential to handle the dataset and model checkpoints during training.