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author | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-11-18 19:34:38 -0700 |
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committer | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-11-18 19:34:38 -0700 |
commit | 3c29f2a6782f1e7b9d0ef2856c6ef6cb6c06c76a (patch) | |
tree | 145b5fbb66f4d5fe636ca566f5f9a32996218ccb | |
parent | 94f732558c9edb8646fd2184f397775662375148 (diff) |
Prepare for new explorations
-rw-r--r-- | README.md | 2 |
1 files changed, 2 insertions, 0 deletions
@@ -4,6 +4,8 @@ This is an exploration of ML models for use in prediction of atomization energie An implementation of most of the ML routine is created from the, mostly, ground up. +* Mostly, the main program is in **ml_exp**, and a new exploration on **other_exp**. + ## Data used * The *QM7* dataset obtained from the [QML tutorial repository](https://github.com/qmlcode/tutorial). This can also be retrieved from the [quantum-machine webpage](http://www.quantum-machine.org/datasets/), but for its use with python, the dataset given by QML is more useful. |