Bidirectional Encoder Representations from Transformers, is a natural language processing (NLP) model developed by researchers at Google.
BERT reads text bidirectionally, allowing it to better understand the context of a word based on its surrounding words. Built on the Transformer architecture, BERT is pre-trained on large corpora of text using unsupervised tasks like masked language modeling and next sentence prediction, enabling it to capture deep linguistic features.
After pre-training, BERT can be fine-tuned for a variety of NLP tasks such as sentiment analysis, question answering, and named entity recognition.
