From Impossible to Irreplaceable: BERT in NLP

Pain Points in NLP: In the NLP domain, to train an ML model, we need a proper dataset that is related to the context of the problem under study. But it's often difficult to get this domain-specific data, and even found it's quite a heavy task to perform labeling. Solution: to tackle this situation, researchers have created a general-purpose model which are trained on the huge unannotated raw texts found on the internet, which includes vast domain's context. BERT is one such solution which can be fine-tuned to any NLP related context prediction. There are multiple algorithms that try to find solutions to NLP problems.