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Applied Machine Learning (AML)

Coursework

Rubric

Your report will be marked according to a number of criteria denoted below, in concert with the quality of the explanation of the report (both text and graphics).

  • task motivation and description
  • relevant background and related previous work
  • exploratory data analysis and data cleaning/filtering
  • discussion of ML methods used and their relevance
  • evaluation measures and results/performance
  • analysis and interpretation of results
  • discussion and conclusions

Marking

While you will be marked out of 100 in line with the [common marking scheme][4], an interpretation of the scheme can be seen as:

70-100
Excellent explanation and description of points above plus extra achievement at understanding or analysis of results. Clear explanations, evidence of creative or deeper thought will contribute to a higher grade.
60-69
Excellent explanation and description of points above, with some minor deficiencies.
50-59
Well explained description of points above, be some deficiencies with writing or work undertaken.
40-49
Sufficient description of points above but significant deficiencies.
30-39
Evidence that the student has gained some understanding, but not addressed the specified task properly.
0-29
Serious error or slack work.