engleski

Machine Learning in Chemistry

Machine learning (ML) approaches are widely used to analyze and model various types of problems, including those related to chemistry. The basic premise is to have a large enough and reliable dataset that is used for training and testing a predictive model. In the presentation, the process of selecting ML methods (like Random Forest or Graph Neural Network) and building predictive models will be demonstrated in the field of design of novel chemicals with biological activities, such as drugs and agrochemicals.

Machine learning ; Chemoinformatics ; QSAR ; biological activities

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