![]() Source: DScribe: Library of descriptors for machine learning in materials science. ![]() Typical workflow to make machine learning predict a property from a molecule. Usually, a descriptor is a number, a vector or a matrix, but other data formats such as character strings are possible. The molecular structures are transformed into descriptors before being used to train the machine learning model, as depicted in the illustration below. ![]() In machine learning, when it comes to predicting the properties of molecules, it is necessary to convert the molecular structures into values that can be used by machine learning algorithms. ![]() Using machine learning to predict properties of molecules or to design molecules with desired properties plays an important role in the field of chemistry, toxicology and materials science. Machine learning descriptors for molecules
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