BERT (Bidirectional Encoder Representations from Transformers)

BERT is a revolutionary natural language processing (NLP) model developed by Google. It is designed to understand the context of words in search queries by looking at the words that come before and after them—bidirectionally—rather than one direction at a time. BERT is a pre-trained model that can be fine-tuned for various NLP tasks such as question answering, sentiment analysis, named entity recognition, and text classification. It has significantly improved the state-of-the-art performance on many NLP benchmarks and is widely used in both academic and industrial applications.