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When to Use Machine Learning

  • Problems that are too complex to be solved by ordinary programming.
  • Problems that involve visual reasoning and language understanding such as image recognition, speech recognition, machine translation, etc
  • Fast changing problems where the characteristics of the problems changes with time, and there is a need to keep the system functioning well.
  • Problems that are clear and have simple goals such as yes/no question or predicting a single continuous number such as the quantity of product likely to be consumed in a given time.

When not to Use Machine Learning

  • You want the predictions made by your model to be fully explainable.
  • You do not have a reliable data for the problem you're trying to solve.
  • You can solve your problem with ordinary programming or a simple heuristic methods.
  • You want a solution that will never need to be updated.