Kur is a descriptive deep learning framework that allows users to define neural network models using simple YAML configuration files rather than writing code. It abstracts away the complexity of backends by supporting Theano, TensorFlow, and PyTorch under a unified interface. The tool provides out-of-the-box multi-GPU training capabilities and includes templating via Jinja2 for rapid experimentation with model variants.