From traditional bag-of-words to modern transformer embeddings
Simple but effective text representation technique
Weighted word importance in document collections
Capturing word order and context through n-gram models
Dense vector representations capturing semantic relationships
Global statistics-based word embeddings
Subword-aware embeddings for handling rare words
Deep contextualized word representations
Transformer-based bidirectional representations
Autoregressive language models for generation
Sentence-level embeddings for semantic similarity
Techniques for visualizing high-dimensional embeddings
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