Businesses around the world are gradually adopting AI/ML models to streamline their workflows and enhance operational efficiencies. Accurately labeled data is the fuel that powers these machines. Thus, a constant flow of precise and high-quality training data becomes an important prerequisite for organizations looking to leverage these futuristic technologies.
As one of the reliable data annotation companies, Data Sprints offers data labeling, image recognition, and data annotation in machine learning, artificial intelligence, autonomous vehicle, robotics, etc. We help businesses with AI data annotation and AI data labeling to improvise the quality of their machine learning algorithm predictions.
With the right blend of experience and skills, we constantly deliver structured, quality, and large volumes of data streams. Our professionals leverage AI data annotation tools to accurately label training datasets. We offer the best turnaround time in the industry for all the outsourced data annotation services. Our professionals provide collaborative workflows to clients in their data labeling outsourcing endeavors. Being one of the leading AI data labeling companies, we have worked across different industry verticals such as Insurance, Healthcare, Retail, and more.
What is Data Annotation in Machine Learning?
Data annotation in machine learning is the process of labeling data available in different forms such as texts, videos, images, etc. The labels are added in the form of tags and metatags that help the natural language processing (NLP) and computer vision-based models to calculate attributes easily.
What are the data annotation prerequisites?
For the machine learning algorithms to make sense out of the big data sets, supervised training is required. Therefore, constant access to voluminous, high-quality, accurate, and relevant datasets is an important prerequisite for data annotation. This is to ensure that the outcomes are reliable and can be used for informed decision-making.
What are the techniques used to annotate different types of data?
Different data modalities require different data annotation techniques. Text annotation techniques include semantic segmentation, entity linking, phrase chunking, etc. Likewise, image and video annotation techniques consist of 2D bounding box annotation, 3D point cloud labeling, polygons, etc.
How to keep a check on the machine learning algorithm’s quality?
Labeling different sets to be fed into the machine learning algorithms requires expertise and time. The absence of accurate labels and human expertise makes attribute computation difficult for smart models. Therefore, human-in-the-loop is essential for AI quality control. The professional providers have competent annotators equipped with state-of-the-art tools to accurately label datasets and ensure quality outcomes.
How can Data Sprint Solutions help you with data annotation tasks?
Data Sprint Solutions offers quality data labeling, image recognition, text annotation services, and video annotation services at cost-effective rates — everything under one roof. We deliver structured, quality, and large volumes of data streams constantly. As one of the leading AI data labeling companies, we have worked across different industry verticals such as Insurance, Healthcare, and Retail. The professionals offer a collaborative workflow to help clients improve the quality of their machine learning algorithm predictions.