There are huge advantages to labeling in-house such as quality control, faster iteration and privacy. New technologies like transfer learning, programmatic labeling and active learning are now making it practical for the best teams.

Humanloop Programmatic is now available for early access. A powerful weak labeling tool to rapidly annotate your NLP datasets.

Weak labeling can replace manually annotated data with data created from heuristic rules written by domain experts. Here I want to explain what weak supervision is, what I learned and why I think it complements techniques like active learning for data annotation.

Human-in-the-loop AI is an automation approach which means you can quickly deploy a working model, with less data and with guaranteed quality predictions. In this post we'll explain what HITL is and how you can make use of this approach in your own AI projects.

Machine learning systems are born through the marriage of both code and data. Academia mostly focuses on ways to improve the learning algorithms, the how of machine learning. When you come to build practical AI systems though the dataset you're training on has at least as much impact on performance as the choice of algorithm.