When you create a model, PerceptiLabs automatically creates and adds both an Input (1) and an Target (2) component to your model:
The Input component represents the input data for your model and points to the .csv file you specified when you created the project. It provides a visualization using the first sample from your input data.
The Target component provides a visualization of the labels / the result we want the model to achieve (e.g., classification).
The screenshot above shows a basic image classification model, where the Input's visualization displays the first image of the input data (an image of the number 7), while the Target's visualization shows the (normalized) probability that that input is classified as 7.