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Outsourced vs Crowdsourced Data Labeling

Outsourced vs Crowdsourced Data Labeling

The success of machine learning projects relies on the quality of data available to train, test, and validate the models.

All significant machine learning challenges can be traced down to the quality and quantity of data available or th…

5 Factors that Make Data Labeling Ineffective

5 Factors that Make Data Labeling Ineffective

A significant hurdle AI/ML projects face is the need to have high-quality data available all the time.

While there is no shortage of raw data, the need to produce usable data remains a big challenge.

  • Automotive companies…