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Machine learning (ML) and artificial intelligence (AI) have had a renaissance during the last few years and have become a hot topic not only in drug discovery but in the whole of society. There are many reasons for the comeback: access to a larger volume of data through automation, faster computers (i.e. GPUs) and methodological progress within deep learning. Drug discovery has also benefited from these trends and, as shown in this book, ML and AI are becoming much more prominent.1  Besides impacting areas that have been using ML for many years such as QSAR modelling, completely new...

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