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Practical guides, research, and industry perspectives from the Annotation.io team — written for ML engineers and AI leaders.
Supervised machine learning involves model training using labeled data. Supervised learning algorithms play an role in our everyday lives, which I have covered in this guide.
Onshore and offshore outsourcing are two techniques of partnering with a third-party service provider. In this guide, I will explain exactly how they differ.
Labeled data contains input values and their corresponding labels. Sounds confusing? Read this blog to get the full picture.
Read this blog and learn all about data annotation quality assurance. You will also find out how to measure quality assurance of a labeled dataset.
Read this guide and learn what manual data labeling stands for. And how is it different from automated data annotation.
Automatic annotation means leveraging AI to speed up the data labeling process. Learn what it is and the role of human annotators in this process.
In this guide I have explained data annotation in detail. You will also get to know the differences between data annotation and data labeling.
Unlabeled Data is raw data without any predefined labels. Learn all about unlabeled data and how this type of data is different than labeled data.
Monthly digest of our best writing on data annotation, ML workflows, and AI industry trends.
