In-House vs Outsourcing Data Annotation for ML: Pros & Cons
In-house data annotation can be expensive but can be helpful in early stages of ML production. Outsourcing data annotation is cheaper but security can be compromised.
pro-related
Sama’s Experiment-Driven Approach to Solving for High-Quality Labels at Scale
A recent academic paper outlines how Sama uses Experiment-Driven Development to measure how improvements made to our platform increase annotation efficiency.
ML Assisted Annotation Powered by MICROMODEL Technology
ML Assisted Annotation can help you generate high-quality pre-labeled and human-assisted annotations, for predictably higher quality data in half the time.
