Machine learning has come a long way since its beginnings in the 30s and 50s. Following advances in statistics, functional analysis, and computing capability, the last decade has seen a burgeoning of applications in the field. This issue of Computing in Science & Engineering presents articles discussing recent advances in the field and their applications to new areas, particularly into solving structured learning problems like drug discovery and experiment design for systems biology. In addition to articles on climate modeling and space weather prediction, the theme articles highlight different application areas and uses of different sets of tools, hinting at the future evolution of machine learning.
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