Manning – Working With Transformer-based Embeddings for Text Similarity Matching

Manning – Working With Transformer-based Embeddings for Text Similarity Matching-iLLiTERATE
English | Size: 0.98 GB
Category: Tutorial

Embeddings from transformer models such as BERT can be used as representations of sentences. In this session, Matteus Tanha works with these embeddings to match similar sentences or paragraphs by exploring a few different distance metrics. The focus is on the application of transformer models but he also goes through the pre-processing steps to extract good quality natural language text.

PEARSON OOWNS MAANY EDU BRAANDS INKLUDINNG
ADDISON-WESLEY PEACHPIT PRENTICE-HALL ECOLLEGE
AND MAANY MORE!

WEE ASUMME NO LIIABILLITY FUR A WROONG SPELING
COZ WEE ARRE A NON (iL)LiTERATE GRUP!!

TANNKS TU THE LITERATE ASKII FRIIEND!!

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nitro.download/view/C385F9C76DA3923/MANNING_WORKING_WITH_TRANSFORMER-BASED_EMBEDDINGS_FOR_TEXT_SIMILARITY_MATCHING-iLLiTERATE.part1.rar
nitro.download/view/B8FE6B6BDF2094C/MANNING_WORKING_WITH_TRANSFORMER-BASED_EMBEDDINGS_FOR_TEXT_SIMILARITY_MATCHING-iLLiTERATE.part2.rar