Machine Learning and Data-Driven Research in Chemistry

This book introduces the conceptual foundations, state-of-the-art techniques, as well as concrete application examples of modern data science in the chemical context. There is a particular focus on the combination of data science and computational studies. Topics covered include: *Knowledge discovery in chemical data: elucidating structure-property relationships and governing principles in chemical systems through modern data science *Features, descriptors, and other representations of chemical systems. Feature selection, feature transformation, and dimension reduction techniques *Statistical and machine learning techniques in data analysis and data mining *Virtual high-throughput screening efforts, big data, and databases in the chemical context *Computational chemistry method developments driven by data science *Technical aspects and software solutions This book introduces the conceptual foundations, state-of-the-art techniques, as well as concrete application examples of modern data science in the chemical context. There is a particular focus on the combination of data science and computational studies. Topics covered include: *Knowledge discovery in chemical data: elucidating structure-property relationships and governing principles in chemical systems through modern data science *Features, descriptors, and other representations of chemical systems. Feature selection, feature transformation, and dimension reduction techniques *Statistical and machine learning techniques in data analysis and data mining *Virtual high-throughput screening efforts, big data, and databases in the chemical context *Computational chemistry method developments driven by data science *Technical aspects and software solutions
 
This book introduces the conceptual foundations, state-of-the-art techniques, as well as concrete application examples of modern data science in the chemical context. There is a particular focus on the combination of data science and computational studies. Topics covered include: *Knowledge discovery in chemical data: elucidating structure-property relationships and governing principles in chemical systems through modern data science *Features, descriptors, and other representations of chemical systems. Feature selection, feature transformation, and dimension reduction techniques *Statistical and machine learning techniques in data analysis and data mining *Virtual high-throughput screening efforts, big data, and databases in the chemical context *Computational chemistry method developments driven by data science *Technical aspects and software solutions This book introduces the conceptual foundations, state-of-the-art techniques, as well as concrete application examples of modern data science in the chemical context. There is a particular focus on the combination of data science and computational studies. Topics covered include: *Knowledge discovery in chemical data: elucidating structure-property relationships and governing principles in chemical systems through modern data science *Features, descriptors, and other representations of chemical systems. Feature selection, feature transformation, and dimension reduction techniques *Statistical and machine learning techniques in data analysis and data mining *Virtual high-throughput screening efforts, big data, and databases in the chemical context *Computational chemistry method developments driven by data science *Technical aspects and software solutions