<ul><li>Language representation techniques have evolved from basic to more context-aware methods.</li><li>Early methods like Bag of Words (BoW) focus on word frequency, while advanced approaches use embeddings and deep learning architectures.</li><li>Embeddings aim to capture semantic relationships and meaning, allowing similar words to be close in vector space.</li><li>The evolution of language representation enables more sophisticated NLP applications that better comprehend human language.</li></ul>

“Evolution of Language Representation Techniques: A Journey from BoW to GPT”

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