Using SageMaker Autopilot in SageMaker Studio

We will build a model using only SageMaker Studio. We won't write a line of machine learning code, so get ready for zero-code AI.

In this section, you'll learn how to do the following:

• Launch a SageMaker Autopilot job in SageMaker Studio.
• Monitor the different steps of the job.
• Visualize models and compare their properties.

Launching a job

First, we need a dataset. We'll reuse the direct marketing dataset used in Chapter 2, Handling Data Preparation Techniques. This dataset describes a binary classification problem: will a customer accept a marketing offer, yes or no? It contains a little more than 41,000 labeled customer samples. Let's dive in:

1. Let's open SageMaker Studio, and create a new Python 3 notebook using the Data Science kernel, as shown in the following screenshot:

   Figure 3.1 – Creating a notebook

2. Now, let's download and extract the dataset as follows...