Boston Housing In-Depth

Now we will look at creating a hyperparameter tuning job using the low level approach. Just like in the other low level approaches, this method requires us to describe the various properties that our hyperparameter tuning job should have.

To follow along, open up the Boston Housing - XGBoost (Hyperparameter Tuning) - Low Level.ipynb notebook in the Tutorials folder.

Creating a hyperparameter tuning job using the low level approach requires us to describe two different things.

The first, is a training job that will be used as the base job for the hyperparameter tuning task. This training job description is almost exactly the same as the standard training job description except that instead of specifying HyperParameters we specify StaticHyperParameters . That is, the hyperparameters that we do not want to change in the various iterations.

The second thing we need to describe is the tuning job itself. This description includes the different ranges of hyperparameters that we do want SageMaker to vary, in addition to the total number of jobs we want to have created and how to determine which model is best.