Implementing a Siamese Network

This guide provides a beginner-friendly implementation of a Siamese network using the MNIST dataset. It covers dataset creation, defining the network, applying contrastive loss, and training the model. The post includes detailed steps for creating image pairs, defining a custom dataset class, and testing the model's performance. Key takeaway: Siamese networks require labeled data, but methods to handle unlabeled data are in discussion.