Machine Learning and Big-Data in Computational Chemistry

Abstract

Experimental chemistry and the younger discipline of computational chemistry have always aspired to increase data volume, velocity, and variety. The recent software developments in machine learning, databases and automation and hardware advances in fast co-processors, networking, and storage have boosted automation and digitization. Computational chemistry is seemingly on the verge of a big-data revolution.