Cheat sheets

We’ve created cheat sheets for some common problem types and some specific use cases. These cheat sheets will guide you through the main steps you take when solving your problem.

Problem types

Multi-label image classification

Use if your input data consists of a set of images (.jpg or .png), where each image can be said to contain or not contain multiple attributes.

Single-label image classification

Use if your input data consists of labeled images containing exactly one of multiple classes.

Image segmentation

Use if you want to mark, pixel by pixel, where a specific type of object is in the image. mark a single object type within an image

Image similarity cheat sheet

Use this cheat sheet if you build projects where you want to find similar images.

Specific use cases

No-code cheat sheet

Use if you want to build an AI model and use it with other no-code tools.

BERT cheat sheet

Use if you want to use BERT and your input data consists of English text with a classification tag.

USE - Text similarity / cheat sheet

The universal sentence encoder, or USE for short, is a text processing model that can encode sentences from 16 different languages. What’s more, the version offered on the Peltarion Platform is pre-trained for sentence similarity tasks.

Snippet selector for image projects

This flowchart will help you select the right snippet for your image data project.