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:target: https://github.com/jgosmann/goppy/actions/workflows/ci.yml
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.. image:: https://codecov.io/gh/jgosmann/goppy/branch/main/graph/badge.svg?token=mkgZs4nds5
:target: https://codecov.io/gh/jgosmann/goppy
.. image:: https://img.shields.io/pypi/v/goppy
:target: https://pypi.org/project/goppy/
:alt: PyPI
.. image:: https://img.shields.io/pypi/pyversions/goppy
:target: https://pypi.org/project/goppy/
:alt: PyPI - Python Version
.. image:: https://img.shields.io/pypi/l/goppy
:target: https://pypi.org/project/goppy/
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.. image:: https://github.com/jgosmann/goppy/blob/main/doc/_static/goppy-sm.png
:alt: GopPy logo
Overview
--------
GopPy (Gaussian Online Processes for Python) is a pure Python module providing
a Gaussian process implementation which allows to add new data efficiently
online. I wrote this module because all other Python implementations I knew did
not support efficient online updates.
The feature list:
* `scikit-learn <http://scikit-learn.org>`_ compatible interface.
* Efficient online updates.
* Prediction of first order derivatives.
* Estimation of the log likelihood and its derivative.
* Well documented.
* `Good test coverage. <https://app.codecov.io/gh/jgosmann/goppy>`_
* MIT license.
Documentation
-------------
The documentation can be found at https://goppy.readthedocs.io/en/latest/.
Installation
------------
You can install GopPy with pip::
pip install goppy
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