What are the advantages of BERT? What are the disadvantages of BERT?

Apr 7, 2025 ... In this article, we will understand the Word Embeddings with their types and discuss all the techniques covered in each of the types of word embeddings. Word embedding is a technique used in natural language processing (NLP) that represents words as numbers so that a computer can work with them. Feb 10, 2025 ... Explain what embeddings are and how they are used in common NLP applications. Present a history of popular methods for training embeddings, ... Jul 5, 2023 ... The Role of Word Embedding in NLP. Word embeddings have revolutionized Natural Language Processing (NLP) by enabling machines to understand ... Jul 7, 2014 ... A word embedding W:words→Rn is a paramaterized function mapping words in some language to high-dimensional vectors (perhaps 200 to 500 ... Feb 10, 2025 ... Word embeddings are dense vector representations of words, allowing NLP models to understand word meanings and relationships efficiently. Jul 8, 2019 ... Intrinsic evaluators test the quality of a representation independent of specific natural language processing tasks while extrinsic evaluators ... Nov 9, 2023 ... A text embedding is a piece of text projected into a high-dimensional latent space. The position of our text in this space is a vector, a long sequence of ... Feb 25, 2023 ... In the field of Natural Language Processing (NLP), the use of word and sentence embeddings has revolutionized the way we analyze and ... We've explored the beginnings of word-based embedding with word2vec and ... That's it for this overview of both the early days of dense vector embeddings in NLP ...