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920c00c Dec 1, 2016
@ai4se @timm
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Many software companies now learn their policies via data-driven methods. Modern practitioners treat every planned feature as an experiment, of which only a few are expected to survive. Key performance metrics are carefully monitored and analyzed to judge the progress of a feature. Even simple design decisions such as the color of a link are chosen by the outcome of software experiments.

This subject will explore methods for designing data collection experiments; collecting that data; exploring that data; then presenting that data in such a way to support business-level decision making for software projects.

News Lectures Homework Review Cool stuff
  1. Ethics
  2. Visualizations
  3. Defect prediction
  4. Privacy
  5. Mistakes
  6. Data reduction
  7. Discretization
  8. Bayes classifiers
  9. Incremental learning
  10. Decision trees
  11. Tables
  12. Stats
  13. Verification studies
  14. Lecture2: Misc
  15. On Average
  16. What is S.O.S.?
  17. Reading12345678
  1. hw8
  2. hw7
  3. hw6
  4. hw5
  5. hw4
  6. Project notes
  7. hw3
  8. hw2
  9. hw1
  1. Review8
  2. Review7
  3. Review6
  4. Review5
  5. Review4
  6. Review3
  7. Review2
  1. Discretization2
  2. Discretization1
  3. Anomaly detection
  4. Bayes nets