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Resources for learning

• Machine Learning Pilot School

Further reading

Quantitative Methods

• Jonathan Stray, A Curious Journalist's Guide to Data, 2016 https://www.gitbook.com/book/towcenter/curious-journalist-s-guide-to-data/details

• John Winn, Christopher Bishop, Thomas Diethe, Model-Based Machine Learning, 2017 http://www.mbmlbook.com/

• Robert E. Kass, Brian S. Caffo, Marie Davidian, Xiao-Li Meng, Bin Yu, Nancy Reid Ten Simple Rules for Effective Statistical Practice http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004961

• William Stafford Noble, A Quick Guide to Organising Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424

Reproducible Research

• Victoria Stodden, Marcia McNutt, David H. Bailey, Ewa Deelman, Yolanda Gil, Brooks Hanson, Michael A. Heroux, John P.A. Ioannidis, Michela Taufer Enhancing reproducibility for computational methods, Science, 354 (6317), pp. 1240-1241, 2016 http://science.sciencemag.org/content/354/6317/1240.full

• Andrew Gelman, Eric Loken, The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf

• James M. Osborne , Miguel O. Bernabeu, Maria Bruna, Ben Calderhead, Jonathan Cooper, Neil Dalchau, Sara-Jane Dunn, Alexander G. Fletcher, Robin Freeman, Derek Groen, Bernhard Knapp, Greg J. McInerny, Gary R. Mirams, Joe Pitt-Francis, Biswa Sengupta, David W. Wright, Christian A. Yates, David J. Gavaghan, Stephen Emmott, Charlotte Deane Ten Simple Rules for Effective Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003506

• Geir Kjetil Sandve , Anton Nekrutenko, James Taylor, Eivind Hovig Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285