Data labeling is an essential step in machine learning. It will allow to identify raw data (images, text files, videos, etc.) and to add one or more meaningful and informative labels to provide a context so that a machine learning model can learn. This is an essential step in machine learning which represents, according to a Cognilytica study, 80% of AI projects.
Find out in this article why you should outsource the annotation of your data to an external task force.
To annotate data, companies can decide to do it in-house or outsource it to a specialized task force.
The workforce you have chosen to classify your dataset is known as the labeling workforce. When you employ an external workforce, you also establish work teams, which are collections of your workforce members who are tasked with carrying out particular tasks. Each task can have one or more work teams assigned to it depending on the project requirements.
A labeling workforce can supply training datasets to teach your computer vision systems to identify lanes and lane markers for determining the drivable area to determine the parking area.
You can create training datasets that assist your autonomous vehicle models in correctly identifying surrounding things.
Labelers can use bounding boxes to annotate traffic signals and signs to make it easier for autonomous vehicle models to recognize these signals.
For retail establishments, data Labelers can provide pixel-level precise product annotation services.
but also :
Text annotation, data processing.. find out more uses cases here
Companies may decide to annotate data in-house or outsource it to a workforce.
Learn about the benefits that exist for each solution :
While in-house labeling is frequently regarded as the pinnacle of data labeling, depending on the phase of your business, it may not always be feasible. If you need to annotate a high volume of data, outsource the labelling but to a reputable data labeling service company or to crowdsource which will have the expertise, all the tools and a trained and qualified workforce.
While there are benefits to crowdsourcing, you frequently wind up spending more time overseeing quality control than you would have otherwise. The benefit of using a data labeling service is that a qualified team handles everything, allowing you to essentially concentrate on other internal initiatives. The best part is that quality is guaranteed and possibly costs less than you expect.
So, if your data requires labeling and it's delaying your AI/ML project, think about consulting with a company like Isahit that offers data labeling services.
Businesses can save money by outsourcing data annotation services rather than recruiting and developing a diverse internal team. The cost of the internal team is high due to the infrastructure, technology, and staff salaries that must be paid.
Compared to the pilot internal team, a third-party service provider provides fast access to an expert team. A skilled team can produce useful datasets for upcoming queries or requirements by understanding the algorithm model of their client. An outsourcing company provides constant accessibility to datasets to train ML algorithms, which aid computers in deciphering the presented digital content's entities.
It is time to use a labeling workforce when:
1. In-house costs are unsustainable and cannot scale: Because of the high worker pay in advanced economies, labeling data internally is particularly expensive. These expenditures can increase to the extent where it is no longer practical to keep labeling in-house for increasingly large datasets. This issue is a common pain point when it comes to internal data labeling.
2. Difficulty recruiting and training labelers: It's not always possible to hire new labelers if your internal labeling team has decreased in size or is insufficient. This is because new personnel need training in order to manufacture labels of a high enough caliber.
The Only Ethical Choice : Isahit is the only data labeling company that places impact at the heart of its model. Convinced that Tech can be a lever for social inclusion, they offer women around the world the opportunity to work remotely and gain skills through free and multidisciplinary training. BCorp certified since 2021, isahit is revolutionizing the world of labeling and data outsourcing by making it ethical.
A wide, diverse and qualify workforce : More than 1500 women are working every day - and as many different profiles - all having the same goal: make your annotation projects a success. They come from 44 countries, speaks 16 languages, cover 5 timezones and have different skills and academic background. In addition, isahit provides them with a very complete and unique training program for each client project. Our culture also supports a broad representation in machine learning, which strengthens the objectivity and ethics of your AI model.
Workforce management platform: Isahit got the most powerful workforce management platform to assist you in developing the best workflow for your projects. This allows us to cut labor expenditures dramatically without sacrificing performance. In reality, the efficient administration of our staff encourages people to produce their best work.
Security : You can rely on Isahit to provide a secure environment free of data security breaches. Since systems with inadequate encryption algorithms are vulnerable to hackers, we are a corporation that prioritizes data protection.
Experience: Many companies undervalue the knowledge or abilities required to provide data labeling services because they believe this is a straightforward task. To avoid human error, which is common but can accumulate and have serious long-term effects, this talent necessitates accuracy and close attention to detail. Due to their lack of adequate resources and equipment to properly label your data, inexperienced providers may potentially incur expensive delays. As of today, isahit have supported more than 350 customers, from various industries and managed more than 4000 Data Labeling projects, from #skinrecognition or #foodrecognition to #predictivemaintenance.In addition, our annotator are highly qualified and experienced in data labeling.
Quality: Quality assurance is a vital aspect of contracting your data labeling. You can be confident that your data is in excellent hands because all of isahit annotators are competent, well-trained, and correctly integrated in the area that your data services. Our staff can adapt rapidly to your requests for workflow adjustments, be open and effective in communicating with you through a tight feedback loop.
You have seen in this article, when it is useful to ask yourself the question of externalization for the labeling of your data. Several solutions exist, but only one prevails if you want to generate a positive impact with annotators and benefit from the best possible quality in your annotations!
In order to assist you in creating machine learning models that perform better, Isahit provides a variety of data labeling services. Some of the biggest brands in the world and the fastest-growing businesses have trusted them as a partner.