This folder contains notebooks for basic usage of the package, e.g. things like dealing with hyperparameters, parameter constraints and priors, and saving and loading models.
Before checking these out, you may want to check out our simple GP regression tutorial that details the anatomy of a GPyTorch model.
- Check out our Tutorial on Hyperparameters for information on things like raw versus actual parameters, constraints, priors and more.
- The Saving and Loading Models notebook details how to save and load GPyTorch models on disk.