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  2. Google Books Ngram Viewer - Wikipedia

    en.wikipedia.org/wiki/Google_Books_Ngram_Viewer

    Google Books Ngram Viewer. The Google Books Ngram Viewer is an online search engine that charts the frequencies of any set of search strings using a yearly count of n -grams found in printed sources published between 1500 and 2022 [1][2][3][4] in Google 's text corpora in English, Chinese (simplified), French, German, Hebrew, Italian, Russian ...

  3. Culturomics - Wikipedia

    en.wikipedia.org/wiki/Culturomics

    Michel and Aiden helped create the Google Labs project Google Ngram Viewer which uses n-grams to analyze the Google Books digital library for cultural patterns in language use over time. Because the Google Ngram data set is not an unbiased sample, [ 5 ] and does not include metadata, [ 6 ] there are several pitfalls when using it to study ...

  4. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1][2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text. T5 models are usually pretrained on a massive ...

  5. Google APIs - Wikipedia

    en.wikipedia.org/wiki/Google_APIs

    Google APIs are application programming interfaces (APIs) developed by Google which allow communication with Google Services and their integration to other services. Examples of these include Search, Gmail, Translate or Google Maps. Third-party apps can use these APIs to take advantage of or extend the functionality of the existing services.

  6. Google Ngram - Wikipedia

    en.wikipedia.org/?title=Google_Ngram&redirect=no

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  7. BERT (language model) - Wikipedia

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

    BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1][2] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture.

  8. Talk:Google Ngram Viewer - Wikipedia

    en.wikipedia.org/wiki/Talk:Google_Ngram_Viewer

    This article was the subject of a Wiki Education Foundation-supported course assignment, between 24 August 2020 and 9 December 2020. Further details are available on the course page. Student editor (s): HaydenMitteer . Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT ( talk) 21:53, 17 January 2022 ...

  9. Search engine indexing - Wikipedia

    en.wikipedia.org/wiki/Search_engine_indexing

    Search engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. An alternate name for the process, in the context of search engines designed to ...