Special Viewpoints

Machine Learning for Science: State of the Art and Future Prospects

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Science  14 Sep 2001:
Vol. 293, Issue 5537, pp. 2051-2055
DOI: 10.1126/science.293.5537.2051

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Abstract

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

  • * To whom correspondence should be addressed. E-mail: mjolsness{at}jpl.nasa.gov

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