add README

Author: mathurinm

README.rst

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+skglm
+========
+
+``skglm`` is a library that provide better sparse generalized linear model for scikit-learn.
+Its main features are:
+
+- **speed**: problems with millions of features can be solved in seconds. Default solvers rely on efficient coordinate descent with numba just in time compilation.
+- **flexibility**: virtually any combination of datafit and penalty can be implemented in a few lines of code.
+- **sklearn API**: all estimators are drop-in replacements for scikit-learn.
+- **scope**: support for many missing models in scikit-learn - weighted Lasso, arbitrary group penalties, non convex sparse penalties, etc.
+
+
+Cite
+----
+
+If you use this code, please cite
+
+.. code-block:: none
+
+    @online{skglm,
+        title={Beyond L1: Faster and Better Sparse Models with skglm},
+        author={Q. Bertrand and Q. Klopfenstein and P.-A. Bannier and G. Gidel and M. Massias},
+        year={2022},
+        url={https://arxiv.org/abs/2204.07826}
+    }
+
+
+
+Installing the development version
+----------------------------------
+First clone the repository available at https://github.com/mathurinm/skglm::
+
+    $ git clone https://github.com/mathurinm/skglm.git
+    $ cd skglm/
+
+Then, install the package with::
+
+    $ pip install -e .
+
+To check if everything worked fine, you can do::
+
+    $ python -c 'import skglm'
+
+and it should not give any error message.