How To Use Synthetic Data To Overcome Data Shortages For Machine Learning Model Training - KDnuggets

The essence of artificial intelligence lies in data. If we don't have sufficient data, we cannot train the models to do what we want, and our expensive and powerful hardware becomes useless. But procuring relevant, accurate, legitimate, and reliable data is easier said than done. That's because the data collection process is often just as complex and time-intensive as setting up the actual machine learning models. Moreover, it also takes time and considerable resources to collect, document, and clean data before it can be used.