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Tags: machine learning

Resources (1-6 of 6)

  1. 50 Years of Data Science

    30 Oct 2018 | Teaching Materials | Contributor(s):

    By David Donoho

    Stanford University

    This paper reviews some ingredients of the current “Data Science moment”, including recentcommentary about data science in the popular media, and about how/whether Data Science isreally different...

  2. An Introduction to Statistical Learning: with Applications in R

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Gareth James1, Daniela Witten2, Trevor Hastie3, Robert Tibshirani3

    1. University of Southern California 2. University of Washington 3. Stanford University

    This book provides an introduction to statistical learning methods and is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.

  3. Artificial Intelligence

    25 Jul 2018 | Teaching Materials | Contributor(s):

    By Kelly O'Donnell

    Science Forward

    This video explores what artificial intelligence is and features people who work on different aspects of intelligence. How do we make machines that think like humans? How can we tell when we’ve...

  4. CyVerse: Scalable Image Informatics

    27 Jul 2020 | Teaching Materials | Contributor(s):

    By Tyson Lee Swetnam1, Edwin Skidmore2, Tony Edgin2, Ramona Walls2, Eric Lyons2, Nirav Merchant2

    1. University of Arizona BIO5 Institute, CyVerse 2. University of Arizona

    Poster on cyberinfrastructure for the machine learning ere presented at the 2020 BIOME Institute: Cultivating Scientific Curiosity

  5. DataCamp

    05 Nov 2018 | Teaching Materials

    DataCamp: The Easiest Way to Learn Data Science Online

  6. The ml4bio Workshop: Machine Learning Literacy for Biologists

    02 Jun 2019 | Teaching Materials | Contributor(s):

    By Fangzhou Mu1, Chris Magnano1, Debora Treu2, Anthony Gitter1

    1. University of Wisconsin - Madison 2. Morgridge Institute for Research

    Presentation on machine learning literacy for biologists at the 2019 Great Lakes Bioinformatics Conference