A list of NLP(Natural Language Processing) tutorials built on Tensorflow 2.0.

Overview

Tensorflow-NLP-tutorial

A list of NLP(Natural Language Processing) tutorials built on Tensorflow 2.0.

위키독스 딥 러닝을 이용한 자연어 처리 입문 의 자연어 처리 튜토리얼 저장소입니다.
기본적으로 딥 러닝 프레임워크 Tensorflow 2.0+을 사용하고 있습니다.

자연어처리_상단_책

코드의 기반이 되는 이론적인 설명은 무료 e-book을 참고바랍니다.

e-book : https://wikidocs.net/book/2155

많은 딥 러닝 또는 자연어 처리 입문자들에게 도움이 되기를 바랍니다.

Colab 실습 방법

각 실습 파일의 py 파일을 열어보면 Colab 링크를 기재해두었습니다.
해당 링크를 Chrome 브라우저에서 복사 + 붙여넣기 하시면 별도 파이썬 설치 바로 실습이 가능합니다.

최신 업데이트 공지

  • 2021년 12월 31일 : 깃허브 저장소를 오픈하였습니다.
Owner
Won Joon Yoo
Machine Learning Engineer
Won Joon Yoo
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Lyrics generation with GPT2-based Transformer

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Local cross-platform machine translation GUI, based on CTranslate2

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Semantic search for quotes.

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A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

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Code for hyperboloid embeddings for knowledge graph entities

Implementation for the papers: Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao,

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📝An easy-to-use package to restore punctuation of the text.

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BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network)

BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a

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Train 🤗transformers with DeepSpeed: ZeRO-2, ZeRO-3

Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.

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