There is no machine learning project without data, so the first step in our analysis is to load the input file (titanic_small.csv) into AMLS. This is a simplified version of the Titanic dataset, which contains three features and one target variable:
- Features:
- pclass: The class in which the passenger traveled (values 1, 2, or 3 corresponding to 1st, 2nd, and 3rd class)
- sex: Passenger's gender (female or male)
- Age group: Infant, child, teenager, adult, elderly, or unknown
- Target variable:
- Survived: 1 if the passenger survived the shipwreck, 0 if they didn't.
To load the file, follow these steps:
- From the home page, click on DATASETS. You will see an empty list of datasets:

- Click on +NEW to get a link to upload a local data file:

- Click on FROM LOCAL FILE and you will see the following dialog box:

- Click on Choose File and navigate...