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rajia rimi
Jun 18, 2022
In Welcome to the Forum
There are several things that make BERT so special for research and beyond (the world - yes, that's as big as a research base for natural language processing). Many of the special Industry Email List features can be found in the title of the BERT article - BERT: Bi-directional Encoder Representations from Transformers. B - bidirectional E - Encoder R - Representations T - Transformers But there are other exciting developments that BERT brings to the field of Industry Email List natural language understanding. These include: Pre-training from unlabeled text Two-way context models The use of a transformer architecture Hidden language modeling Focused attention Text implication (next sentence prediction) Disambiguation through open-source context Pre-training from unlabeled text The 'magic' of BERT is its implementation of two-way training on a corpus Industry Email List of unlabeled text since for many years in the field of natural language understanding, collections of text had been labeled manually by teams of linguists assigning different parts of speech Industry Email List to each. word. BERT was the first natural language framework/architecture to be pre-trained using unsupervised learning on pure plain text (2.5 billion words+ from English Wikipedia) rather than tagged corpora. Earlier models required manual hose earlier approaches are similar to the markup we mentioned earlier by Google Pygmalion. BERT learns the language by understanding the cohesion of the Industry Email List text from this large body of raw text content, and then it is further educated by refining smaller, more specific natural language tasks. BERT also learns itself over time. Two-way context models BERT is the first deeply bidirectional natural language model, but what does it mean? Bidirectional and Industry Email List unidirectional modeling True contextual understanding comes from being able to see all the words in a sentence at once and understanding how all the
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rajia rimi

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