Organizational Adoption of Synthetic Data

 Synthetic Data in Machine Learning: What, Why, How?

Synthetic data generation must address several aspects of data quality issues for AI algorithms. For example, from the information quality perspective, we might need to deal with bias or data availability, scaling, or coverage. On the other hand, a careful data-centric analysis can produce tremendous results that cover many ethical, #explainability, and verification issues. Perhaps the more challenging problem is the democratization of synthetic data and organizational adoption of synthetic data-based solutions in corporate environments. #algorithms #quality #ai #data #syntheticdata #bias #ethicalAI #responsibleai #machinelearning

https://mltechniques.com/2022/07/24/synthetic-data-in-machine-learning-what-why-how