Data Curation

Create datasets that work

in the real world

Properly curated Machine learning datasets can be the difference between a ML system that works in the real world and one that stays in the lab.

Dataset Curation Flow
Data curation edge cases

Create robust, trustworth AI systems

Complex AI systems need to be trained for unusual but possible situations in order to be robust.

Make sure that your ML systems can handle the most sticky situations by including important edge-cases in your datasets.

Data curation clean datasets

Only train your models on clean data

Gargage-in garbage out. Raw datasets can have a large number of bad samples, due to bad lighting, occlusion, blurred vision etc.

Make sure your ML models are trained only on clean and relevant data samples.