Machine learning for science: State of the art and future prospects

Recent advances in machine learning methods, along with successful applicat ions across a wide variety of fields such as planetary science and bioinfor matics, promise powerful new tools for practicing scientists. This viewpoin t highlights some useful characteristics of modern machine learning methods and their relevance to scientific applications. We conclude with some spec ulations on near-term progress and promising directions.