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Working with transformer-based embeddings for text similarity matching

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...

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Bibliographic Details
Format: eBook
Language:English
Published: [Place of publication not identified] Manning Publications 2021
Edition:[First edition]
Subjects:
Natural Language Processing
Natural Language Processing (computer Science) / Fast / (ocolc)fst01034365
Traitement Automatique Des Langues Naturelles
Natural Language Processing (computer Science) / Http://id.loc.gov/authorities/subjects/sh88002425
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary: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
Physical Description:1 video file (22 min.) sound, color

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