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-# lj_matrix
+# lj_exp
 
-This is an exploration of a representation (or descriptor), based on the Lennard-Jones potential, for use in prediction of atomization energies (and possibly other properties) of molecules using Machine Learning (ML).
+This is an exploration of ML models for use in prediction of atomization energies (and possibly other properties) of molecules using Machine Learning (ML).
 
-An implementation of existing representations (for now only Coulomb matrix), this new representation and most of the ML routine is created from the, mostly, ground up.
+An implementation of most of the ML routine is created from the, mostly, ground up.
 
 ## Data used
 
@@ -10,4 +10,4 @@ An implementation of existing representations (for now only Coulomb matrix), thi
 * The *QM9* dataset is obtained from the [quantum-machine webpage](http://www.quantum-machine.org/datasets/), but it's slightly modified for its use with python.
 * On the other hand, the *periodic table of elements* data was retrieved from [this handy Gist](https://gist.github.com/GoodmanSciences/c2dd862cd38f21b0ad36b8f96b4bf1ee).
 
-*NOTE*: This is not supposed to be a python package (for now), but rather, the basis for future work. Please give credit if you use(d) the code presented here (contact me for more).
+*NOTE*: This is not supposed to be a python package (for now), but rather, the basis for future (personal) work.