Uhrs: Crowdsourced data-labelling platform.

and operate AI solutions to drive immediate business impact.
Our Center of Excellence methodology and the RapidMiner Academy ensures customers are successful, regardless of their experience or resource levels.
Simplify operations, regardless of how complex models are, or how they were created.
Deploy, evaluate, compare, monitor, manage and swap any model.
Solve your organization issues faster with sharper insights and predictive models, no-one understands the business enterprise problem as if you do.

In addition, it harnesses the wisdom of the crowd from all over the globe.
Gartner ranked Toloka as one of the most notable data labeling solutions available in the market in its Hype Cycle for Data Science & ML report.
Innotescus is an image and video annotation platform that enables collaboration and data handling.
It streamlines Computer Vision development through intuitive collaboration features, smart annotation tools and seamless data handling.
Its data visualization tools and cross functional collaboration features help identify data bias early and improve data accuracy.
This allows for faster and more cost-efficient deployments of high-performance Artificial Intelligence.

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Learn how Sense makes it easy for AI/ML teams to create and deploy AI IoT answers to any cloud, the edge or on-premise.
Raise the model accuracy with a pre-trained DNN model for auto-labeling.
It is an open platform

To guarantee the confidentiality of client data, our facilities and teams have been certified by ISO and PCI DSS .
We adhere to the main industry security standards, such as GDPR and CCPA.
Cogito shoulders AI enterprises and business initiatives by deploying a proficient workforce for data annotation, content moderation and any data processing services.
Our data enrichment services provide one-stop solutions for all your data-related needs.
Our scalable, immensely experienced, brilliant minds unite their knowledge to meet your requirements swiftly with precise accuracy while maintaining full data security and confidentiality.
Our mission is to help our customers innovate and scale by solving their day-to-day data needs.

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Playment offers various data annotation services, nonetheless it is apparently focused solely on the automotive industry.
Still, many large companies trust the business, which provides an in depth description of the various data annotation projects it could manage.
This is somewhat out of the ordinary, since few companies have a tendency to elaborate on the forms of data annotations they specialize in.

This tool also allows data scientists to train and validate object detection models.
Data labeling may be the process of adding target attributes to training data and labeling them so that a machine learning model can learn what predictions it really is expected to make.
This process is one of the stages in preparing data for supervised machine learning.
While labeling isn’t launching a rocket into space, it’s still serious business.
Labeling can be an indispensable stage of data preprocessing in supervised learning.
Historical data with predefined target attributes can be used because of this model training style.
An algorithm can only find target attributes in case a human mapped them.

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Lionbridge offers human-labeled data in hundreds of applications.
Lionbridge AI has over 20 years experience as a trusted way to obtain training data.
This allows businesses large and small to build, test, and enhance their machine learning models.
Our global community of qualified contributors provides usage of large amounts of data in every languages and file formats.
The all-in-one data annotation platform that supports text, audio, images, and video.
Our advanced crowd system makes it possible to automatically distribute projects to qualified contributors so that you can begin immediately.

Rapid, guided iteration of the training data is required to develop and deploy AI types of high quality.
Versioning and auditing data like code leads to faster and more ethical deployments.
By collaborating on a standard interface, which provides the info essential to train models, subject material experts could be integrated.
Reduce risk and ensure compliance by labeling programmatically, and not sending data to external annotators.
Appen combines the intelligence of over one million people around the world with cutting-edge algorithms to create the very best training data for the ML projects.
Upload your data to your platform, and we’ll provide all the annotations and labels necessary to create ground truth for your models.

“We have yet to grapple in virtually any substantive way with how they completely reorient the vast majority of people with this planet to how they work,” she said.
There are so many applications that I don’t think we’ll be running out of this work any time in the future,” he said.