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  1. #1

  2. #2
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    Google BERT stands for Bidirectional Encoder Representations from Transformers and is an update to the core search algorithm aimed at improving the language understanding capabilities of Google.7 days ago

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    “Bert is a natural language processing pre-training approach that can be used on a large body of text. It handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. Bert helps Google understand natural language text from the Web.

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    BERT is the first fine- tuning based representation model that achieves state-of-the-art performance on a large suite of sentence-level and token-level tasks, outper- forming many task-specific architectures. ... The code and pre-trained mod- els are available at https://github.com/ google-research/bert.

  5. #5
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    BERT is a method of pre-training language representations, meaning that we train a general-purpose "language understanding" model on a large text corpus (like Wikipedia), and then use that model for downstream NLP tasks that we care about (like question answering).

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  6. #6
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    Bert is a natural language processing pre-training approach that can be used on a large body of text. It handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. Bert helps Google understand natural language text from the Web.

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    It's Google's neural network-based technique for natural language processing (NLP) pre-training. BERT stands for Bidirectional Encoder Representations from Transformers. It was opened-sourced last year and written about in more detail about the Google AI blog.

  8. #8
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    BERT, which stands for Bidirectional Encoder Representations from Transformers, is a neural network-based technique for natural language processing pre-training. In plain English, it may be used to assist Google better identify the context of words from search queries.

  9. #9
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    Bidirectional Encoder Representations from Transformers (BERT) is a technique for NLP (Natural Language Processing) pre-training developed by Google. BERT was created and published in 2018 by Jacob Devlin and his colleagues from Google. Google is leveraging BERT to better understand user searches.
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  10. #10
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    BERT, which stands for Bidirectional Encoder Representations from Transformers, is a neural network-based technique for natural language processing pre-training. In plain English, it can be used to help Google better discern the context of words in search queries.

  11. #11
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    BERT is a Bidirectional Encoder Representations from Transformers, this is a google algorithm update which is useful for google to understand the search query words.
    Last edited by Jessicad0505; 12-20-2019 at 02:00 AM.

  12. #12
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    BERT, which stands for Bidirectional Encoder Representations from Transformers, is a neural network-based technique for natural language processing pre-training. In plain English, it can be used to help Google better discern the context of words in search queries.

  13. #13
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    BERT, which stands for Bidirectional Encoder Representations from Transformers, is a neural network-based technique for natural language processing pre-training. In plain English, it can be used to help Google better discern the context of words in search queries.

  14. #14
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    BERT stands for Bidirectional Encoder Representations from Transformers. According to the official explanation from Google, it's a “neural network-based technique for natural language processing (NLP) pre-training.” Despite that rather complex description, the basic premise of this update is relatively simple.

  15. #15
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    Bert is a natural language processing pre-training approach that can be used on a large body of text. It handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. Bert helps Google understand natural language text from the Web.

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