What is BERT?

BERT (Bidirectional Encoder Representations from Transformers) is a transformer-based machine learning technique for natural language processing (NLP). It is pre-trained on a large corpus of text and can be fine-tuned for various downstream tasks, such as question answering, text classification, and natural language inference. BERT's key innovation is its ability to consider the context of a word from both its left and right sides, leading to a better understanding of meaning.