# Introduction

This section collects machine-learning tutorials on universal relations for neutron stars, with examples ranging from rapidly rotating configurations to neural-network descriptions of stellar surfaces and higher-order multipole relations.

The material is drawn from three tutorial repositories:

- [UR-for-rotating-NS-using-ML-](https://github.com/gregoryPapi/UR-for-rotating-NS-using-ML-): universal relations for rapidly rotating neutron stars.
- [Universal-description-of-the-NS-surface-using-ML](https://github.com/gregoryPapi/Universal-description-of-the-NS-surface-using-ML): neural-network regressors for neutron-star surface quantities.
- [deep-universal-relations](https://github.com/gregoryPapi/deep-universal-relations): deep-learning models for universal relations involving moments of inertia, quadrupole moments, spin octupoles, and related quantities.

The notebooks are provided by Grigorios Papigkiotis and Georgios Vardakas.