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GPy - A Gaussian Process (GP) framework in Python
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Introduction
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`GPy <http://sheffieldml.github.io/GPy/> `_ is a Gaussian Process (GP) framework written in Python, from the Sheffield machine learning group.
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The `GPy homepage <http://sheffieldml.github.io/GPy/> `_ contains tutorials for users and further information on the project, including installation instructions.
This documentation is mostly aimed at developers interacting closely with the code-base.
The code can be found on our `Github project page <https://github.com/SheffieldML/GPy> `_ . It is open source and provided under the BSD license.
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Installation
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For developers
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- `Writing new models <tuto_creating_new_models.html> `_
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- `Writing new kernels <tuto_creating_new_kernels.html> `_
- `Write a new plotting routine using gpy_plot <tuto_plotting.html> `_
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- `Parameterization handles <tuto_parameterized.html> `_
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API Documentation
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.. toctree ::
:maxdepth: 1
GPy.models
GPy.kern
GPy.likelihoods
GPy.mappings
GPy.examples
GPy.util
GPy.plotting.gpy_plot
GPy.plotting.matplot_dep
GPy.core
GPy.core.parameterization
GPy.inference.optimization
GPy.inference.latent_function_inference
GPy.inference.mcmc
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Indices and tables
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------------------
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* :ref: `genindex`
* :ref: `modindex`
* :ref: `search`
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