Data labeling is one of the most tedious and time-consuming processes in the lifecycle of your Artificial Intelligence (AI) or Machine Learning (ML) models. The performance of AI and ML models depends on the accuracy of the training data. However, many often don’t realize that there is a big factor that contributes to the accuracy score of a training dataset — the people behind the data labeling tasks.
There are three common methods to getting your training data labeled. You could work with:
- An in-house data labeling team
- Crowdsourced individuals
- A data labeling company
What is a data labeling company?
A data labeling company typically handles the end-to-end process that goes into data labeling. From identifying your project needs, recruiting and assembling a workforce of labelers, to supplying a suite of labeling tools. In certain cases, some companies also offer the flexibility to work on your proprietary data labeling platform.
The main distinction between a data labeling company and a crowdsourced team of individuals is a data labeling company watches over the entire labeling process on your behalf, allowing you to be relatively hands-off on the project. Most would have some form of quality assurance and quality control assurance in place so that everything is checked before it gets sent back to you.
As for crowdsourced individuals, you are solely responsible for recruiting, training, and managing the group of data labelers that you have put together. While you may have more control over the exact people who work on your project, you would need to spend significantly more time on making sure that your project gets done exactly the way you want it.
In choosing the right data labeling solution
There are many factors that come into play – when choosing the right data labeling partner as the quality of your training data hinges on who you trust to execute the work.
We recommend taking as much time as you can to consider your options as there are many available in the market who may offer seemingly similar services, but differ on the finer details such as the ability to scale, flexibility, pricing, security, and QA & QC process. Rushing into a decision or not performing enough due diligence could result in loss of money and time as a low-quality set of training data cannot be used at all and must be reworked.
Before you start choosing a solution
The process of getting your data labeled by an external party – crowdsourced individuals or a labeling company – can be streamlined by first being prepared yourself.
Whether you are sourcing for new options or in the process of renewing your contract with your existing partner, it’s always important to be able to communicate exactly what you’d like to get out of your arrangement.
Throughout our years of working with clients from around the world, we’ve identified 10 important steps to prepare you for your engagement with a data labeling partner. This would serve as a good foundation to ensure a smooth communication process that will end in high-quality data labeling.
Remember, the best way to maximize the return on your investment is to go into it prepared.
To read more, download our latest E-book and learn more about how you can mitigate the risks of working with a third-party partner and end up with data that you can actually use.
Are you ready to engage a Data Labeling Partner?