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 see our simple GP regression notebooks that detail the anatomy of a GPyTorch model here.
- 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.