- High-Quality AI And Machine Learning Data Labeling At Scale: A Brief Research Report - Jul 25, 2019.
Analyst firm Cognilytica estimates that as much as 80% of machine learning project time is spent on aggregating, cleaning, labeling, and augmenting machine learning model data. So, how do innovative machine learning teams prepare data in such a way that they can trust its quality, cost of preparation, and the speed with which it’s delivered?
- Crowdsourcing vs. Managed Teams: A Study in Data Labeling Quality - Jun 12, 2019.
You need data labeled for ML. You can do it in-house, crowdsource it, or hire a managed service. If data quality matters, read this.