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Project Summary

At the end of your project report, please provide a summary of the emphasis/priorities in your project. Give yourself a total of 20 point in these categories:

  • Getting the data: Acquiring/gathering/downloading.
  • ETL: Extract-Transform-Load work and cleaning the data set.
  • Problem: Work on defining problem itself and motivation for the analysis.
  • Algorithmic work: Work on the algorithms needed to work with the data, including integrating data mining and machine learning techniques.
  • Bigness/parallelization: Efficiency of the analysis on a cluster, and scalability to larger data sets.
  • UI: User interface to the results, possibly including web or data exploration frontends.
  • Visualization: Visualization of analysis results.
  • Technologies: New technologies learned as part of doing the project.

Total: 20

Don't think of this as giving yourself a mark. (That's our job.) This is intended to be a guide for our marking, so we don't miss significant work you did. (e.g. if you give yourself 6 points on new technologies and we haven't noticed any, we know to keep looking; if you gave yourself 0 then we can move on and look at other aspects.)

Since this will be guiding our marking, you may want to address these areas in your report as well.

You will likely be giving yourself 0 in some of these categories: that's perfectly reasonable. You aren't expected to do all of these, but should (of course) have done some subset of them (including bigness which we expect you to think about).

[If there are other categories you think should be here, ask us.]

Updated Fri Aug. 25 2023, 15:55 by ggbaker.