Transfer learning for better AI models with less data

Transfer learning (TL) is an often-used technique in machine learning that helps you train better AI models. It was used to create accurate universal ML models for computational chemistry – AIQM1 (Nat. Commun. 2021, 12, 7022) and ANI-1ccx (Nat. Commun. 2019, 10, 2903).

In our online tutorial, we show how to do transfer learning with MLatom.

There, we also provide a Jupyter notebook that you can run on the XACS Jupyter lab and experiment yourself with this powerful machine learning technique. For this, you need to register on the XACS cloud (free).

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