This repository provides a vanilla implementation of Neural Turing Machines in PyTorch. An NTM extends traditional sequence processors (like LSTMs) with an external differentiable memory bank, allowing the network to learn algorithmic tasks and maintain internal state longer than standard recurrent networks. The implementation supports batch learning, flexible read/write head configurations, and includes copy and repeat-copy task experiments that reproduce results from the original NTM paper.