Summary

SageMaker Data Wrangler is a purpose-built tool specifically for analyzing and processing data for machine learning. It is also one of the foundational platforms for machine learning on AWS. This has been a long chapter, and although we covered several key features of Data Wrangler, there are still a few features that we left out of this book. We started by looking at how to log in to SageMaker Studio and access Data Wrangler. For the sample dataset, we used the built-in Titanic dataset that is available via a public S3 bucket. We imported this dataset into Data Wrangler via the default sampling method. We then performed EDA, first by using the built-in insights report in Data Wrangler and then by adding additional analysis, including using our custom code. Next, we defined several data transformation steps for our Data Wrangler flow to do feature engineering. For this, we used several built-in data transformations in Data Wrangler. We also looked at applying a custom data...