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Tags: deep learning* + bert* + nlp* + classification* + machine learning*

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1. BEAL: A Bayesian Deep Active Learning Method for Efficient Deep Multi-Label Text Classification

   BEAL is a deep active learning method that uses Bayesian deep learning with dropout to infer the model’s posterior predictive distribution and introduces an expected confidence-based acquisition function to select uncertain samples. Experiments show that BEAL outperforms other active learning methods, requiring fewer labeled samples for efficient training.

   2024-11-18 Tags: beal, bayesian, deep learning, active learning, multi-label, text, classification, bert, machine learning by klotz
2. Feature Extraction with BERT for Text Classification | by Marcello Politi | Jun, 2022 | Towards Data Science

   2022-07-11 Tags: bert, classification, text, nlp, machine learning, deep learning, embedding by klotz
3. Zero-Shot Intent Classification with Siamese Networks | by Duygu ALTINOK | Sep, 2021 | Towards Data Science

   2021-09-25 Tags: bert, intent, classification, deep learning by klotz
4. Topic Modeling with BERT. | Towards Data Science

   2020-12-08 Tags: topic modeling, bert, classification, nlp, embedding, deep learning, tf-idf, clustering, marten grootendorst by klotz
5. Multi Class Text Classification With Deep Learning Using BERT | by Susan Li | Aug, 2020 | Towards Data Science

   2020-08-03 Tags: bert, nlp, classification, deep learning, text by klotz
6. Classifying Scientific Papers with Universal Sentence Embeddings

   2020-01-04 Tags: classification, abstracts, embedding, bert, deep learning by klotz
7. “Introducing FastBert — A simple Deep Learning library for BERT Models”

   2019-06-05 Tags: bert, nlp, text, pytorch, fastbert, classification, embedding, deep learning by klotz

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