BERT
Bidirectional Encoder Representations from Transformers, a pre-trained language model for NLP tasks.
In-depth explanation
BERT (2018) revolutionized NLP by pre-training a transformer encoder on masked language modeling and next sentence prediction. Unlike previous models that read text left-to-right, BERT reads bidirectionally, capturing context from both directions. BERT is fine-tuned for downstream tasks like classification, QA, and NER, achieving state-of-the-art results.
Examples
Related terms
More in Natural Language Processing
Natural Language Processing (NLP)
The field of AI focused on enabling computers to understand, interpret, and generate human language.
Tokenization
Breaking text into smaller units (tokens) such as words, subwords, or characters.
Word Embedding
Dense vector representations of words that capture semantic meaning and relationships.
Named Entity Recognition (NER)
Identifying and classifying named entities in text into categories like person, organization, location.
Sentiment Analysis
Determining the emotional tone or opinion expressed in text, typically positive, negative, or neutral.
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