One of the most important applications of synthetic data is its use in developing machine learning solutions – to train and test machine learning models – when real data is hard to collect or sensitive to share. For that reason, it is...
Data Engineering vs Machine Learning the differences and overlaps Data quality is critical to both Data Engineering and Data Science, after all poor quality data can be costly quite costly for a business. Accordingly to Gartner poor data...
As organizations increasingly rely on synthetic data to improve their machine learning models, ensuring that the relations like pairwise distributions and correlations are kept in synthetic data is part of the fidelity assessment whenever...
