Deciding what to Try Next

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Deciding what to Try Next
  • Should be expected by now average expert of machine learning
  • Know truly what algorithm for each problem

  • What to do when the result is largely different from the actual output
  • Prioritize small subset of feature, more impotance ones
  • lambda(regularization parameters)
  • Unfortunately, most common are choosing by instinct, not by science
  • Choosing which avenues by these simple method
  • These techniques will part the correct way from the rest of the avenues
  • Next two videos, evaluate learning algorithm, and next discuss about this technique
  • Insight from the test of which promising way to try
  • Diagnostic can be time consuming, but still worthed compared to spend many months only to find out that the avenues that we choose is wrong

  • Next try few things to improve machine learning system