There is no straight answer to that question, since different models may require different dataset sizes. In general, the more complex the algorithm is, the more data you'll need to receive satisfactory results. That's why, for the neural network to work well, you'll need much more data than in the case of simple machine learning classification models. However, it's not only about the size of the dataset, but also its quality. If you feed your model with much low-quality data, you cannot expect an accurate outcome. But worry not – even if your dataset is limited, we can try to extend it by applying data augmentation technique.