Machine learning

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Across
  1. 3. One complete pass through the entire training dataset
  2. 4. The ability of a model to perform well on new, unseen data
  3. 6. A step-by-step procedure that computers follow to solve problems
  4. 8. When a model performs too well on training data but poorly on new data
  5. 9. A systematic error that occurs in machine learning predictions
Down
  1. 1. Basic processing unit in artificial neural networks, inspired by brain cells
  2. 2. The process of teaching a model using historical data
  3. 3. A measurement of how wrong a model's predictions are
  4. 5. The process of splitting input data into smaller subsets for training
  5. 7. A mathematical representation that makes predictions based on input data