Lecture4-Supervised1

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Across
  1. 2. helps us to reduce the cost function to reach minima
  2. 6. The sample of data used to provide an unbiased evaluation of a model fit on the training dataset while tuning model hyperparameters
  3. 7. is a machine learning model can be used to predict the recovery time, based on symptoms & medical history of patients
Down
  1. 1. helps us to get the best values for a0 and a1
  2. 3. is the difference between the average prediction of our model and the correct value which we are trying to predict
  3. 4. is opposite algorithm to One R
  4. 5. is the error that appears with too complex models