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A high-bias, low-variance introduction to Machine Learning for physicists.

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Title: A high-bias, low-variance introduction to Machine Learning for physicists.
Authors: Mehta P; Department of Physics, Boston University, Boston, MA 02215, USA., Wang CH; Department of Physics, Boston University, Boston, MA 02215, USA., Day AGR; Department of Physics, Boston University, Boston, MA 02215, USA., Richardson C; Department of Physics, Boston University, Boston, MA 02215, USA., Bukov M; Department of Physics, University of California, Berkeley, CA 94720, USA†., Fisher CK; Unlearn.AI, San Francisco, CA 94108., Schwab DJ; Initiative for the Theoretical Sciences, The Graduate Center, City University of New York, 365 Fifth Ave., New York, NY 10016.
Source: Physics reports [Phys Rep] 2019 May 30; Vol. 810, pp. 1-124. Date of Electronic Publication: 2019 Mar 14.
Publication Type: Journal Article
Journal Info: Publisher: North-Holland Pub. Co Country of Publication: Netherlands NLM ID: 9876465 Publication Model: Print-Electronic Cited Medium: Print ISSN: 0370-1573 (Print) Linking ISSN: 03701573 NLM ISO Abbreviation: Phys Rep Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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        Value: 10.1016/j.physrep.2019.03.001
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