Neural Networks

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Across
  1. 4. This is produced by the output layer.
  2. 7. A function that adds non-linearity to a neural network.
  3. 8. What training data is used for when modeling.
  4. 10. The initial settings applied when creating a model before specialized tuning.
  5. 11. When noise is fit by a neural network, you have ___ the data.
Down
  1. 1. Weights are added to neural networks using this.
  2. 2. A type of validation that creates a single training and testing split.
  3. 3. Inspiration for neural networks
  4. 5. Purpose of a loss function (There is an underscore for a space between two words)
  5. 6. This happens when the learning rates are too high.
  6. 9. The layer that receives raw input in a neural network.