Data is gold. It is the lifeblood of machine learning models. But what happens when the access is limited? Is this where synthetic data can step up? Tech Republic brought this interesting information to our attention in their article, “Synthetic data: The future of machine learning.”

Synthetic data is artificially generated by an artificial intelligence (AI) algorithm that has been trained on a real data set. It has the same predictive power as the original data but replaces it rather than disguising or modifying it. The goal is to reproduce the statistical properties and patterns of an existing data set by modeling its probability distribution and sampling it out.

In the past, a lack of data has led to the convenient approach of using a randomly generated set of data points. Although this may have been sufficient for educational and testing purposes, random data is not something you would want to train any kind of prediction model from. This is where synthetic data is different. It is reliable data and that is important.

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Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

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