No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Adding Training Data

This video tutorial covers a machine learning project using Amazon SageMaker Canvas. It begins with an introduction to the project and the data sourced from the UCI Machine Learning repository, focusing on banknote authentication. The data attributes include variance, skewness, kurtosis, and entropy, with class labels indicating genuine or forged notes. The tutorial explains how to split the data into training and test sets, upload it to SageMaker Canvas, and manage datasets, including deletion and status checks. It also covers options for joining datasets within the Canvas interface.

What steps are involved in adding data to SageMaker Canvas?

What options are available for joining datasets in the Canvas interface?