From 30024b72b2b70ec57bb69d866a62fd1836f14852 Mon Sep 17 00:00:00 2001
From: jacoterh <54140851+jacoterh@users.noreply.github.com>
Date: Wed, 2 Nov 2022 16:15:41 +0100
Subject: [PATCH] updating README.md

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 # ML4EFT
-Studies of ML for EFT applications
+ML4EFT is a general open-source framework for the integration of unbinned multivariate observables into global fits of particle physics data.
+It makes use of machine learning regression and classification techniques to parameterise high-dimensional likelihood ratios,
+and can be seamlessly integrated into
+global analyses of, for example, the Standard Model Effective Field Theory and Parton Distribution Functions.
+
+The ML4EFT framework is made available via the Python Package Index (pip) and can be installed directly 
+by running 
+
+``pip install ml4eft``
+
+or alternatively the code can be downloaded from this public GitHub repository, and then installed by running
+
+```shell
+cd code
+pip install -e .
+```  
+
+The framework is documented on a dedicated website
+https://lhcfitnikhef.github.io/ML4EFT,
+where, in addition, one can find a self-standing tutorial (which can also
+be run in Google Colab) where the user is guided step by step in how
+unbinned multivariate observables can be constructed given a choice of
+EFT coefficients and of final-state kinematic features.
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