Lecture 12 - data-ppf/data-ppf.github.io GitHub Wiki

Lecutre 12: Data Science as a Trading Zone

  1. (excerpt from) Galison, Peter. "Computer simulations and the trading zone." The disunity of science: Boundaries, contexts, and power (1996): 118-157.

This article by Galison establish the Trading Zone metaphor in understanding how new fields are constructed from different communities, each with their own languages and values. Please read only:

  • introduction and "Simulations" (pp118-121)
  • "The Pidgin of Monte Carlo"(pp151-157)
  1. Cleveland, William S. "Data science: an action plan for expanding the technical areas of the field of statistics." International statistical review 69, no. 1 (2001): 21-26.

In the line of heretical statiscticians from Bell; here Cleveland proposes a new field

  1. Jones, Matthew L. "Querying the Archive: Data Mining from Apriori to PageRank." Science in the Archives: Pasts, Presents, Futures (2017): 311.

  2. Hammerbacher, Jeff. "Information platforms and the rise of the data scientist." Beautiful Data (2009): 73-84.

Optional readings

  1. Donoho, David. "50 Years of Data Science." Journal of Computational and Graphical Statistics 26, no. 4 (2017): 745-766.

  2. Luhn, Hans Peter. "A business intelligence system." IBM Journal of Research and Development 2, no. 4 (1958): 314-319.

2017:

Readings for April 11

(cf., https://data-ppf.slack.com/archives/C3SJQ5FH9/p1491620769670344 ).

This week the theme is "Technology and data: databases & deep learning"

Readings are:

  1. databases: The chapter from Jeff Hammerbacher which we started on Thursday morning (posted in slack at https://data-ppf.slack.com/files/chris/F4VEQADT6/hammer-chapter.pdf )

  2. databases: A preprint chapter from our own Professor Jones ( https://data-ppf.slack.com/files/chris/F4VNZTBDE/jones_querying_archive_uncorrected_proof.pdf )

  3. deep learning: A review from Yann Lecun and Geoff Hinton ( https://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf )

OPTIONAL:

  1. a very conversational piece on the impact of deep learning on translation, from The New York Times Magazine, from December: "The Great AI awakening" https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html

  2. a very conversational piece on the impact of deep learning on the medical profession, particularly radiology, by Columbia's own Siddhartha Mukherjee: "A.I. VERSUS M.D." in The New Yorker, from Last week: http://www.newyorker.com/magazine/2017/04/03/ai-versus-md