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Building a Sentiment Classification System With BERT Embeddings: Lessons Learned

The MLOps Blog

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing.

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2022: We reviewed this year’s AI breakthroughs

Applied Data Science

Dall-e , and pre-2022 tools in general, attributed their success either to the use of the Transformer or Generative Adversarial Networks. The former is a powerful architecture for artificial neural networks that was originally introduced for language tasks (you’ve probably heard of GPT-3 ?) Who should I follow? What happened?

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Best Large Language Models & Frameworks of 2023

AssemblyAI

These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications. They use neural networks that are inspired by the structure and function of the human brain. How Do Large Language Models Work?

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The State of Transfer Learning in NLP

Sebastian Ruder

In contrast, current models like BERT-Large and GPT-2 consist of 24 Transformer blocks and recent models are even deeper. The latter in particular finds that simply training BERT for longer and on more data improves results, while GPT-2 8B reduces perplexity on a language modelling dataset (though only by a comparatively small factor).

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ML and NLP Research Highlights of 2021

Sebastian Ruder

6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. For each input chunk, nearest neighbor chunks are retrieved using approximate nearest neighbor search based on BERT embedding similarity. Advances in Neural Information Processing Systems, 2020. Why is it important?   wav2vec 2.0:

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Major trends in NLP: a review of 20 years of ACL research

NLP People

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. Especially pre-trained word embeddings such as Word2Vec, FastText and BERT allow NLP developers to jump to the next level. Neural Networks are the workhorse of Deep Learning (cf. Vaswani, N.

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