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DOC add anaconda installation info (#5)
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joaopfonseca committed Apr 22, 2022
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<a href="https://github.com/joaopfonseca/ml-research/actions/workflows/ci.yml"><img alt="Github Actions" src="https://github.com/joaopfonseca/ml-research/actions/workflows/ci.yml/badge.svg"></a>
<a href="https://codecov.io/gh/joaopfonseca/ml-research"><img alt="Codecov" src="https://codecov.io/gh/joaopfonseca/ml-research/branch/master/graph/badge.svg?token=J2EBA4YTMN"></a>
<a href="https://mlresearch.readthedocs.io/en/latest/?badge=latest"><img alt="Documentation Status" src="https://readthedocs.org/projects/mlresearch/badge/?version=latest"></a>
<a href="https://badge.fury.io/py/ml-research"><img alt="Pypi Version" src="https://badge.fury.io/py/ml-research.svg"></a>
<a href="https://pepy.tech/project/ml-research"><img alt="Downloads" src="https://pepy.tech/badge/ml-research"></a>
<a href="https://github.com/psf/black"><img alt="Black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
<a href="https://img.shields.io/badge/python-3.8%20|%203.9-blue"><img alt="Python Versions" src="https://img.shields.io/badge/python-3.8%20|%203.9%20|%203.10-blue"></a>
<a href="https://doi.org/10.3390/RS13132619"><img alt="DOI" src="https://zenodo.org/badge/DOI/10.3390/RS13132619.svg"></a>
</p>
<table align="center">
<tr>
<td>
<b>PyPI</b>
</td>
<td>
<a href="https://badge.fury.io/py/ml-research"><img alt="Pypi Version" src="https://badge.fury.io/py/ml-research.svg"></a>
<a href="https://pepy.tech/project/ml-research"><img alt="Downloads" src="https://static.pepy.tech/personalized-badge/ml-research?period=total&units=international_system&left_color=grey&right_color=brightgreen&left_text=downloads"></a>
</td>
</tr>
<tr>
<td>
<b>Anaconda</b>
</td>
<td>
<a href="https://anaconda.org/conda-forge/ml-research"><img alt="Conda Version" src="https://img.shields.io/conda/vn/conda-forge/ml-research.svg"></a>
<a href="https://anaconda.org/conda-forge/ml-research"><img alt="Conda Downloads" src="https://img.shields.io/conda/dn/conda-forge/ml-research.svg"></a>
</td>
</tr>
</table>

``ML-Research`` is an open source library for machine learning research. It
contains the software implementation of most algorithms used or developed in
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### User Installation

If you already have a working installation of numpy and scipy, the easiest way
to install scikit-learn is using ``pip`` :
The easiest way to install ml-research is using ``pip`` :

pip install -U ml-research

Or ``conda`` :

conda install -c conda-forge ml-research

The documentation includes more detailed [installation
instructions](https://mlresearch.readthedocs.io/en/latest/getting-started.html).

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make environment
conda activate mlresearch # Adapt this line accordingly if you're not running conda

# Install project requirements and the research package
pip install .[tests,docs]
# Install project requirements and the research package. Dependecy group
# "all" will also install both dependency groups shown below.
pip install .[tests,docs]

## Citing ML-Research

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