Data Labeling

Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.

NLP is one of the most difficult AI applications to develop and maintain. When you outsource data labeling, make sure you choose the right team.

Optical character recognition (OCR) can improve productivity when transcribing text, but people still play a critical role in quality control.

What will 2021 bring to the world of AI and machine learning? CloudFactory CEO and founder Mark Sears shares our predictions.

CloudFactory’s project managers lead teams that deliver client work. Meet one of our leaders in Nairobi, Kenya, and read about a typical day for her.

Data preparation is the most time-consuming part of machine learning. Here are a few tips for getting it right.

Agriculture data is complex. Annotating agtech data often requires help from agronomists. We help Hummingbird Tech overcome that AI product development hurdle.

Some data annotation tools won't be a good fit for your AI and machine learning project. Keep these six important features in mind as you evaluate tool providers.

Supervised learning requires a lot of labeled data. Here’s what it takes to design a high-performance data labeling pipeline for machine learning.

Even in uncertain times, you’re swimming in an ocean of data. If you’re using AI, how you process and use that data will determine the future of your business.

Your in-house data scientists shouldn't be doing tedious data labeling work for machine learning projects. They should be focusing on more important innovation.

Not all outsourced data labeling partners are a good fit for every AI project. Here are 5 things you need to consider before, during, and after vendor evaluations.

The data annotation. One emerging feature is automation, also known as pre-annotation or auto labeling. This article will focus on some of its benefits and drawbacks.

It takes a lot of time and resources to prepare and label data. Learn why outsourcing the data preparation to a managed workforce partner is a good business decision.

The level of data quality you'll receive from data labeling providers depends on several workforce, QA and tooling factors. Here are 6 ways some data labeling providers put your ...

The people, processes, and tools used by outsourced data labeling partners make a big difference in final data quality. Here are 3 signs that you'll receive quality work from your ...