*Infpy* is a python package I have put together that implements some of the algorithms I (John Reid)
have used in my research. In particular it has a Gaussian process package that is largely based on
the excellent book, Gaussian Processes for Machine Learning by Rasmussen and Williams.

The Gaussian process package is the only infpy package that is extensively documented so far but you are welcome to try out the others. The Gaussian process package has the following attributes:

*noisy*data is easily modelled- many different
*kernels*are supported out of the box allowing many models to be tested - kernel
*composition*(point-wise sum and product) is intuitive permitting rapid model evaluation *maximum likelihood*estimation of hyper-parameters facilitates model comparison*numpy*integration allows easy interoperability with other python scientific toolkits- high quality
*matplotlib*plots are easy to create - best of both worlds : ease of using an interpreted language but all performance critical linear algebra performed in
*compiled code*