Overview

The Lightly Worker internally uses our open-source Lightly Framework to allow you to use self-supervised learning in a straightforward and efficient way and even create embeddings of your unlabeled data. However, we can do much more than just train and embed datasets. Once you have embeddings of your data, you might still require some labels to train a model. But which samples do you pick for labeling and training a model?

This is exactly why we built the Lightly Platform. The platform helps you analyze your unlabeled data, keep track of your dataset and, by using various methods, pick the relevant samples for your task.

The video below gives you a quick tour of the platform:

Core Concepts

• Datasets
• Tags
• Samples

Analyze and Filter

• Metadata
• Correlation
• Embeddings

Advanced

• Export
• Metadata Configuration

Additional Concepts

Further concepts of the Lightly Platform can be found in our Glossary