AutoMLConfig.py

# Create the configuration for the experiment
from azureml.train.automl import AutoMLConfig

# See https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig?view=azure-ml-py for details
automl_config = AutoMLConfig(
        task='regression',                                  # regression, classification, or forecasting
        training_data=ds,                                   # The data to use to train the model
        label_column_name='thingIWantToPredict',            # The column we're trying to predict
        n_cross_validations=3,                              # How many cross-validation sets to use
        primary_metric='normalized_root_mean_squared_error',# The metric we use to compare model performance
        compute_target=cpu_cluster,                         # Where the experiment should be run
        max_concurrent_iterations=max_nodes,                # How many models can be trained simultaneously
        iterations=40,                                      # The total number of models to train
        iteration_timeout_minutes=5                         # The amount of time before giving up on a single model training run
    )