GPy
a Gaussian processes framework in python
This project is maintained by SheffieldML
GPy
GPy is a Gaussian Process (GP) framework written in python, from the Sheffield machine learning group.
Gaussian processes underpin range of modern machine learning algorithms. In GPy, we've used python to implement a range of machine learning algorithms based on GPs.
GPy is available under the BSD 3-clause license. We'd love to incorporate your changes, so fork us on github!
Installation
Installation instructions along side the source code can be found on the GPy project github page. The instructions vary slightly with the target OS but essentially revolve around installing from the python package index, PyPI
Documentation
You can read the online documentation for GPy here:
Tutorials
A series of tutorials on working with GPy can be found here: These are in the ipython notebook format: the code, plots and text can be read online. If you wish to run the examples locally they can be downloaded and run with the ipython notebook.User mailing list
If you have any questions about the project, or require any help working with the code please make sure you are signed up the the
Tests
As the code is under active development we try to ensure that the code is well tested using Continuous Integreation. We'd love to here of any bugs you have found so please do submit issues through our GPy issues page. Continuous integration status is currently: