Synthetic Data Description, Benefits and Implementation
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The quality and volume of data are critical to the success of AI algorithms. Real-world data collection is expensive and time-consuming. Furthermore, due to privacy regulations, real-world data cannot be used for research or training in most situations, such as healthcare and the financial sector. Another disadvantage is the datau2019s lack of availability and sensitivity. To power deep learning and artificial intelligence algorithms, we need massive data sets.<br><br>Synthetic data, a new area of artificial intelligence, relieves you of the burdens of manual data acquisition, annotation, and cleaning.
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Synthetic Data Description, Benefits and Implementation
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