Creating your first machine learning model

Finally, we will now build our first ML model to predict customer churn events. As this is our first machine learning model, let’s use the simple CREATE MODEL command. This option uses Amazon SageMaker Autopilot, which means, without the heavy lifting of building ML models, you simply provide a tabular dataset and select the target column to predict and SageMaker Autopilot automatically explores different solutions to find the best model. This includes data preprocessing, model training, and model selection and deployment. AutoMode is the default mode:

1. Redshift ML shares training data and artifacts between Amazon Redshift and SageMaker through an S3 bucket. If you don’t have one already, you will need to create an S3 bucket. To do this, navigate to the Amazon S3 console and click on the Create bucket button:

Figure 5.3 – S3 console

2. On the Create bucket page, under Bucket name...