What is BERTs?

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 data and can then be fine-tuned for specific NLP tasks like question answering, text classification, and named entity recognition. BERT's key innovation is its ability to consider the context from both the left and right sides of a word when understanding its meaning, making it highly effective at capturing nuances in language.