This talk will be about the Gaussian process (GP) functionality in the open source Python package PyMC, and how to use GPs effectively for models in the real world. The goal will be to bridge the (wide!) gap between theory and practice, using an example from baseball. By the end of the talk you'll know what's possible in PyMC and how to avoid common pitfalls.