When to use machine learning

Machine learning is not magic and it may be not be beneficial to all data-related problems. It is important at the end of this introduction to clarify when machine-learning techniques are extremely useful:

  • It is not possible to code the rules: a series of human tasks (to determine if an e-mail is spam or not, for example) cannot be solved effectively using simple rules methods. In fact, multiple factors can affect the solution and if rules depend on a large number of factors it becomes hard for humans to manually implement these rules.
  • A solution is not scalable: whenever it is time consuming to manually take decisions on certain data, the machine-learning techniques can scale adequately. For example, a machine-learning ...

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