There are various types of neural networks, each suited for different problems, from basic feed forward networks to advanced transformer models. When tackling fraud detection, the approach can vary based on data availability; unsupervised techniques are useful for unlabeled data, while labeled data allows for traditional supervised learning. The quality of data labeling plays a crucial role in the effectiveness of machine learning solutions.
