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  2. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus.

  4. List of forms of word play - Wikipedia

    en.wikipedia.org/wiki/List_of_forms_of_word_play

    Techniques that involve semantics and the choosing of words. Anglish: a writing using exclusively words of Germanic origin; Auto-antonym: a word that contains opposite meanings; Autogram: a sentence that provide an inventory of its own characters; Irony; Malapropism: incorrect usage of a word by substituting a similar-sounding word with ...

  5. fastText - Wikipedia

    en.wikipedia.org/wiki/FastText

    fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. [3] [4] [5] [6] The model allows one to ...

  6. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. [ 1 ] A prompt is natural language text describing the task that an AI should perform. [ 2 ]

  7. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Word2vec is a word embedding technique which learns to represent words through self-supervision over each word and its neighboring words in a sliding window across a large corpus of text. [28] The model has two possible training schemes to produce word vector representations, one generative and one contrastive. [27]

  8. Play Hearts Online for Free - AOL.com

    www.aol.com/games/play/masque-publishing/hearts

    Enjoy a classic game of Hearts and watch out for the Queen of Spades!

  9. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word. For instance, whereas the vector for "running" will have the same word2vec vector representation for both of its occurrences in the ...