Machine Learning and NLP

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[Machine Learning and NLP @ML_NLP]

Are you interested in Machine Learning and NLP? Subscribe and contribute to the Natural Language Processing community on Reddit https://t.co/Ic0TTWXBCl #NLProc #MachineLearning

[Machine Learning and NLP @ML_NLP]

Building a Faster and Accurate Search Engine on Custom Dataset with Transformers 🤗 https://t.co/1m4pKR04QE #NLProc

[Machine Learning and NLP @ML_NLP]

A visual guide to regular expressions https://t.co/02h4jS3kI8

[Machine Learning and NLP @ML_NLP]

GraphGlove: embedding words in non-vector space with unsupervised graph learning https://t.co/yviw9mItwx #NLProc

[Machine Learning and NLP @ML_NLP]

The return of nearest neighbor models —or memory-based learning— to NLP: strong gains on neural MT, especially for domain adaptation https://t.co/PLmVXT6GFP #NLProc

[Machine Learning and NLP @ML_NLP]

How can we make language models be less data-hungry? https://t.co/fX8m4Yd2r4 #NLProc

[Delip Rao @deliprao]

For my next word sense disambiguation class #nlproc

[Machine Learning and NLP @ML_NLP]

Advancing NLP with efficient projection-based model architectures https://t.co/riHn8jSYeQ #NLProc

[Machine Learning and NLP @ML_NLP]

It's not just size that matters: small language models are also few-shot learners https://t.co/at3Ii2R9JE #NLProc

[Machine Learning and NLP @ML_NLP]

A Comparison of LSTM and BERT for Small Corpus https://t.co/lnbRGKYkVs #NLProc

[Machine Learning and NLP @ML_NLP]

Language Interpretability Tool (LIT): a visual, interactive model-understanding tool for NLP models https://t.co/NQxNks6Y9O #NLProc

[Machine Learning and NLP @ML_NLP]

Paraphrase Generation as Zero-Shot Multilingual Translation https://t.co/BegzVJEMGM #NLProc

[Machine Learning and NLP @ML_NLP]

Word2vec Skip-gram Dimensionality Selection via Sequential Normalized Maximum Likelihood https://t.co/7lxWQUBnnz #NLProc

[Machine Learning and NLP @ML_NLP]

Large-scale Transfer Learning for Low-resource Spoken Language Understanding https://t.co/HO9gmzsq6a #NLProc

[Machine Learning and NLP @ML_NLP]

Zero-Shot Learning in Modern NLP https://t.co/UKq8ROLUWG #NLProc

[Machine Learning and NLP @ML_NLP]

Sentiment Analysis using Deep Learning https://t.co/5RffiRg0T8 #NLProc

[Machine Learning and NLP @ML_NLP]

Big Bird: Transformers for Longer Sequences https://t.co/l5isSLk0gW #NLProc

[Machine Learning and NLP @ML_NLP]

Numpy Cheat Sheet https://t.co/yJSWtsm59C #DataScience

[Machine Learning and NLP @ML_NLP]

GPT-3, a Giant Step for Deep Learning and NLP https://t.co/77iO8LdDoj #NLProc

[Machine Learning and NLP @ML_NLP]

Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods https://t.co/9KoptxYimk #NLProc

[Machine Learning and NLP @ML_NLP]

Advances of transformer-based models for news headline generation https://t.co/lSr38lfQRS #NLProc