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Machine learning applications in chemistry have been booming during the last few years, and data‐driven prediction in organic synthesis witnessing a revolution. Targeting the reactions’ performances, the implementation of reaction knowledge has provided a bridge for the promotion of more sophisticated and accurate machine learning. Herein, we highlight recent, representative advances in embedding...
Recent years have witnessed a boom of machine learning (ML) applications in chemistry, which reveals the potential of data‐driven prediction of synthesis performance. Digitalization and ML modelling are the key strategies to fully exploit the unique potential within the synergistic interplay between experimental data and the robust prediction of performance and selectivity. A series of exciting studies...
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