Bi-LSTM-CRF is a model architecture that combines bidirectional Long Short-Term Memory (LSTM) networks with Conditional Random Fields (CRF) for sequence labeling tasks, particularly in natural language processing. This architecture effectively captures contextual information from both directions in the input data and improves the prediction accuracy of tasks like named entity recognition by considering the relationships between labels in sequences.
congrats on reading the definition of bi-lstm-crf. now let's actually learn it.