Source: thenewstack.io
Pre-Labeled Datasets Are Key to Building High-Quality ML Models
As artificial intelligence scales, data privacy becomes even more important in developing https://thenewstack.io/machine-learning-models-to-predict-the-next-stranger-things/. So the biggest question remains: How do you get the data you need to build the models while also respecting data privacy?
Data providers tend to have a wide selection of pre-labeled datasets that can be used to train ML models.
Labeled data can be used to train ML models to detect and subsequently remove PII from unlabeled datasets.
These datasets can then be used to train ML models to remove personally identifiable information prior to the start of the data annotation process.
Data providers tend to have a wide selection of pre-labeled datasets that can be used to train ML models.
Labeled data can be used to train ML models to detect and subsequently remove PII from unlabeled datasets.
These datasets can then be used to train ML models to remove personally identifiable information prior to the start of the data annotation process.
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