Data Collection as a Service

Improper Data is a significant barrier to efficient machine learning. Hence, data collection has recently become a hotly debated issue in the global tech community for primarily two reasons. The first reason is that as machine learning is employed more often, we are witnessing new applications that may not have enough labeled data. Second, deep learning algorithms, unlike conventional ML techniques, automatically produce features, saving on feature engineering expenses but potentially requiring more annotated data.