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Home / Glossary / Data labeling

What is Data labeling?

Data labeling is the process of tagging raw data with meaningful annotations to enable machine learning models to recognize patterns. It is crucial in supervised learning applications such as image recognition, NLP, and speech processing.

Related Glossaries

  • Data-informed decision-making Data-informed decision-making balances data insights with human expertise and contextual knowledge. It integrates analytical findings with qualitative inputs to create a more comprehensive decision-making process.
  • AI alignment AI alignment refers to the challenge of ensuring that AI systems act in accordance with human intentions and values. Research in AI alignment seeks to prevent AI from taking actions that could be harmful or misaligned with societal goals.
  • Internet of Things The Internet of Things (IoT) connects physical devices, sensors, and software to exchange data over the internet. IoT is used in smart homes, healthcare, industrial automation, and connected vehicles, driving digital transformation and real-time decision-making.
  • AI Data Refinement AI Data Refinement refers to the ongoing process of improving data so it becomes more usable, reliable, and execution-ready for AI systems. It typically includes diagnosis, repair, augmentation, standardization, and state control.
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