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Simply described, a dataset in machine learning is a collection of data bits that may be considered as a single unit by a computer for analytic and prediction purposes. This means that the data gathered should be homogeneous and understandable to a machine that does not see data in the same manner that people do.

To teach machine learning algorithms how to execute various tasks, training datasets must be given into the algorithm first, followed by validation datasets (or testing datasets) to check that the model is correctly understanding the data.

To teach machine learning algorithms how to execute various tasks, training datasets must be given into the algorithm first, followed by validation datasets (or testing datasets) to check that the model is correctly understanding the data.

Machine Learning's Benefits:

  • Identifies trends and patterns quickly.
  • No need for human interaction (automation)
  • Ongoing Improvement
  • Managing data that is multi-dimensional and diverse.
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