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51 lines
1.4 KiB
ReStructuredText
51 lines
1.4 KiB
ReStructuredText
GPy - A Gaussian Process (GP) framework in Python
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=================================================
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Introduction
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------------
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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.
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This documentation is mostly aimed at developers interacting closely with the code-base.
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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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------------
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For developers
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--------------
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- `Writing new models <tuto_creating_new_models.html>`_
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- `Writing new kernels <tuto_creating_new_kernels.html>`_
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- `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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-----------------
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.. toctree::
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:maxdepth: 1
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GPy.models
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GPy.kern
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GPy.likelihoods
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GPy.mappings
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GPy.examples
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GPy.util
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GPy.plotting.gpy_plot
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GPy.plotting.matplot_dep
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GPy.core
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GPy.core.parameterization
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GPy.inference.optimization
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GPy.inference.latent_function_inference
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GPy.inference.mcmc
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Indices and tables
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------------------
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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