[ML] Machine Learning

Machine Learning

  • Modeling (What): the process of creating a model to understand how the collected data interact in an specified environment
  • Trial and Error (How): the process of making guesses about what will happen, measuring the output, and updating the model accordingly
  • Predictions (Why, Goal): making correct predictions with new data
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[ML] Machine Learning Lifecycle

Machine Learning builds the mathematical model (algorithm) to make predictions without explicit programming based on the sample (training) data.

Machine Learning Lifecycle is the process that defines each step that an organization can follow to take advantage of machine learning and artificial intelligence (AI) to achieve practical business value.

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