1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
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Updated
Nov 29, 2024 - Python
1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
It's Smart-Question Answering System on short as well as long documents. It can automatically find answers to matching questions directly from documents. The deep learning language model converts the questions and documents to semantic vectors to find the matching answer.
Named Entity Recognition
A curated list of papers and experiments in the field of Natural Language Processing (NLP)
Apply Bi-LSTM with self-attention, attached CRF for Named Entity Recognition.
Example of usage several NLP algorithms to create summary of political topic articles from web.
Tutorials for recommender system
The proposed model is able to predict the evaluation of both grammatical coherence, vocabulary and grammatical conventions, so that the evaluation can give each of those criteria a value between 1 and 5, I did not treat the system as a classification process, but rather it was treated as a REGRESSION issue
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