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Lab: Hyperparameter Tuning Preparation

Preparing your notebook for hyperparameter tuning involves:

  1. Moving all relevant tracking metrics to the final cell of a notebook and tagging this cell with Pipeline Metrics.
  2. Skipping all unnecessary cells so you only focus on the relevant model.

In the prior walk through you began this exercise and now in this lab you will finish the work you began.


This lab has two requirements. First you must finish preparing the Pipeline Metrics cell. To do this you must:

  1. Add print(xgb_sq_err) to the final cell
  2. Add print(xgb_sq_log_err) to the final cell
  3. Tag the cell with Pipeline Metrics

Second you must finish skipping unnecessary cells. To do this tag the Random Forest model cells with Skip.


View Solution

The final cell in the notebook should look like this: pipeline metrics defined

The skipped cells should look like this: skipped models

Once you have completed this lab please proceed to the next page.