Selecting the right Machine Learning problem

This post is very boring, there are just questions and no answers.

I will start with 2 questions:

  1. Which problem of my organization is the right one that investing on Machine Learning solution I will capture valuable return?
  2. What are the features of a problem that makes it the appropriate one for a ML solution?

The answers:

For question #1, I do not have an answer. For question #2 I learned some suggestions from book Enterprise Artificial Intelligence and Machine Learning for Managers.

  1. The problem are tractable with a reasonable scope and solution times.
  2. Unlock sufficient business value and can be operationalized so you can capture the value.
  3. Address ethical considerations.

Other secondary questions:

  1. Do we have enough data to track the problem?
  2. Do we know the economic value of the problem?
  3. Can we measure the performance of the business function where we pretend to apply the Machine Learning solution with respect a baseline?
  4. Do we have data sets that are fair?
  5. Does have our potential solution the right balance with between fairness and bias?
  6. Did we take into account potential safety issues?
  7. Can the solution approach being explainable?
  8. Is the solution approach transparent and easily understandable?
  9. What is the advantage of using a Machine Learning solution instead of another solution?
  10. Can we classify different issues or business cases in terms of priority?
  11. Do the different business cases have relation with others?

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