New model to naturally detect depression in conversations

Link: http://news.mit.edu/2018/neural-network-model-detect-depression-conversations-0830

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Discovering and Classifying In-app Message Intent at Airbnb

An article on how #AirBnB finds intent in conversations to make its service better.

Link: https://medium.com/airbnb-engineering/discovering-and-classifying-in-app-message-intent-at-airbnb-6a55f5400a0c

#NLP #intent
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Efficient multi-lingual language model fine-tuning

Most of the worlds text is not in English. To enable researchers and practitioners to build impactful solutions in their domains, understanding how our NLP architectures fare in many languages needs to be more than an afterthought.
In this post, we introduce our latest paper that studies multilingual text classification and introduces #MultiFiT, a novel method based on #ULMFiT.

MultiFiT, trained on 100 labeled documents in the target language, outperforms multi-lingual BERT. It also outperforms the cutting-edge LASER algorithm-even though LASER requires a corpus of parallel texts, and MultiFiT does not.

Post: http://nlp.fast.ai/classification/2019/09/10/multifit.html
Paper: https://arxiv.org/abs/1909.04761
Tweet: https://twitter.com/seb_ruder/status/1186744388908654597?s=20

#NLP #DL #FineTuning
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#Lecture for CMU CS, Neural Networks for #NLP 2017
http://goo.gl/QyDGbo
#MachineLearning
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#Lecture for CMU CS, Neural Networks for #NLP 2017
http://goo.gl/QyDGbo
#MachineLearning
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New model to naturally detect depression in conversations

Link: http://news.mit.edu/2018/neural-network-model-detect-depression-conversations-0830

#nlp #audio #dl
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@offerspot and Webseries and movies Get more
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Deep learning to translate between programming languages

#FacebookAI released TransCoder, an entirely self-supervised neural transcompiler system that is claimed to make code migration easier and more efficient.

ArXiV: https://arxiv.org/pdf/2006.03511.pdf
Github: https://github.com/facebookresearch/TransCoder/

#NLU #codegeneration #NLP