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Whether your ML model works off static images, raw videos or 3D LiDAR - our experienced team can prepare the necessary training data for you.
exploreSpeech within call logs or audio files. Sentiments within Tweets or Facebook posts. Text within images or documents. Your ML tool can be fed on text or audio - we got you covered either way.
exploreFor any repetitive tasks or remote clerical operations you need automated or outsourced, we have the people who can help you out.
exploreExperienced labellers on-premise and from the crowd give you flexibility regarding speed of deliveryand any specialisation or security needs!
All of our labelers are trained on project parameters before assignment, and our in-house QA managers vet every instance before submitting data back to you!
There are a wide range of annotation platforms & tools out there. We ensure the tools best-suited for your use-case are used on your project.
Researchers, students & startups love us – because we help train models quickly, without breaking the bank! High-quality human labelling at less than $5/ hour!
Data labeling is a crucial step in any supervised machine learning task. Labeling is the process of defining areas in an image and generating text descriptions for those regions. Different computer vision annotation tools help us make data more readable for computer vision. Labeling images plays an important role to ensure the quality of data. It also helps create datasets for different experiments.
As a seasoned provider of labeling services ourselves, the price tag seemed exorbitantly high. There's a difference between making a healthy margin and taking clients for a ride. This got me thinking of the many different ways labeling providers are billing clients more than they need to. Here are 9 ways clients end up paying more for labeling services than they should have:
Data processing is a milestone that has been achieved in the technological era, especially for the training of AI and machine learning. When an organization has a massive amount of data, it needs the right data labeling workforce that caters to its needs. When planning to choose the right personnel for the duty, it should have the following information for the decision-making process;
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