Data annotation guides
Teams buying labeling work get Guides on checking label quality, running QA, which security to request and comparisons of two companies or tools. People searching for annotation work can use the last two guides.
Quality metrics for labels:worked examples for measuring if returned labels are correct.
A QA workflow for data annotation.How to review the labels one step at a time and what a small trial job should test.
Security and compliance for data labeling:the audits and laws every company and platform lists, each with a source link, plus the papers to request.
Guides for buying data annotation
- Quality metrics for labels: worked examples for measuring if returned labels are correct.
- A QA workflow for data annotation. How to review the labels one step at a time and what a small trial job should test.
- Security and compliance for data labeling: the audits and laws every company and platform lists, each with a source link, plus the papers to request.
- Outsourcing data labeling: contracts, small trial jobs and costs if your data is labeled by another company.
- Scale AI vs Surge AI: a direct comparison.
- A side-by-side look at Scale AI vs Appen.
- Appen vs TELUS Digital: a side-by-side look at both.
- Labelbox vs V7 Darwin: a side-by-side look at Labelbox vs V7 Darwin.
- The two most used free labeling tools compared: CVAT vs Label Studio.
- Top data annotation tools: open-source options compared on license, formats and whether you can host them yourself.
Guides for annotators
- Jobs in data annotation: who hires annotators and the pay to expect.
- Data Annotation Tech review: it looks at whether this platform is legit and the pay on offer.