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Machine Learning AUC Fall-2017

Jupyter Notebook 100.00%
machine-learning machine-learning-coursera notebook-jupyter numpy pandas

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feedback ass2

Total 14.25 out of 15 = 95%
Written assignment: 4.75/5

  • see the solutions online

Programming assignment: 9.5/10

  • very well done
  • nice modular code
  • your search space for parameter c could have been bigger
  • a bit more in depth written analysis would be better

grading ass1

Total: 12.5/15
Programming assignment: 9.5/10

  • always plot axes names on a plot!
  • get rid of the code that you don't use, those commented out print statements shouldn't be there
  • analysis ok, but some minor improvements, like:
  • for overfitting those are good solutions, but do you need them at all? are you overfitting?
  • you could have make a table for alphas, or even make a plot.
  • very good score because of the spitted cost function, nice one!

Written assignment: 3/5

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