# Index * [소개글](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/master) * [서문](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/preface) * [Index](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/index_list) * [딥러닝을 활용한 자연어 처리 개요](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover) * [자연어 처리란 무엇일까?](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover/01-intro) * [딥러닝 소개](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover/02-deeplearning) * [왜 자연어 처리는 어려울까?](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover/03-why-nlp-difficult) * [무엇이 한국어 자연어 처리를 더욱 어렵게 만들까?](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover/04-korean-is-hell) * [자연어 처리의 최근 추세](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover/05-trends) * [기초 수학](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1) * [서문](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/01-intro) * [랜덤 변수와 확률 분포](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/02-prob-dist) * [쉬어가기: 몬티 홀 문제](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/03-monty-hall) * [기대값과 샘플링](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/04-sampling) * [Maximum Likelihood Estimation](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/05-mle) * [정보 이론](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/06-information) * [쉬어가기: MSE 손실 함수와 확률 분포 함수](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/07-mse) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-1/08-conclusion) * [Hello 파이토치](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-2) * [딥러닝을 시작하기 전에](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-2/01-intro) * [설치 방법](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-2/02-how-to-install) * [짧은 튜토리얼](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-2/03-hello-pytorch) * [쉬어가기: 윈도우즈 개발 환경 구축](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-2/04-how_to_install_wins) * [전처리](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3) * [전처리란](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/01-intro) * [코퍼스 수집](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/02-collecting-corpus) * [코퍼스 정제](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/03-cleaning-corpus) * [분절](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/04-tokenization) * [병렬 코퍼스 정렬](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/05-align) * [서브워드 분절](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/06-bpe) * [분절 복원](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/07-detokenization) * [토치텍스트](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-3/08-torchtext) * [유사성과 모호성](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4) * [단어의 의미](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/01-intro) * [One-hot 인코딩](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/02-one-hot-encoding) * [시소러스를 활용한 단어 의미 파악](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/03-wordnet) * [특징](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/04-feature) * [특징 추출하기: TF-IDF](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/05-tf-idf) * [특징 벡터 만들기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/06-vectorization) * [특징 유사도 구하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/07-similarity) * [단어 중의성 해소](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/08-wsd) * [Selectional Preference](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/09-selectional-preference) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-4/10-conclusion) * [단어 임베딩](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/01-intro) * [차원 축소](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/02-dimension-reduction) * [흔한 오해 1](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/03-myth) * [Word2Vec](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/04-word2vec) * [GloVe](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/05-glove) * [Word2Vec 예제](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/06-example) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-5/07-conclusion) * [시퀀스 모델링](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/01-intro) * [Recurrent Neural Network](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/02-rnn) * [Long Short Term Memory](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/03-lstm) * [Gated Recurrent Unit](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/04-gru) * [그래디언트 클리핑](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/05-gradient-clipping) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-6/06-conclusion) * [텍스트 분류](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7) * [들어가기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/01-intro) * [나이브 베이즈를 활용하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/02-naive-bayes) * [흔한 오해 2](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/03-myth) * [RNN을 활용하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/04-rnn) * [CNN을 활용하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/05-cnn) * [쉬어가기: 멀티 레이블 분류](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/06-multi_classification) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-7/07-conclusion) * [언어 모델링](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/01-intro) * [n-gram](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/02-n-gram) * [언어 모델의 평가 방법](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/03-perpexity) * [SRILM을 활용한 n-gram 실습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/04-srilm) * [NNLM](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/05-nnlm) * [언어 모델의 활용](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/06-application) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-8/07-conclusion) * [신경망 기계번역](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/01-intro) * [Sequence-to-Sequence](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/02-seq2seq) * [Attention](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/03-attention) * [Input Feeding](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/04-input-feeding) * [자기회귀 속성과 Teacher Forcing 훈련 방법](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/05-teacher-forcing) * [탐색(추론)](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/06-beam-search) * [성능 평가](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/07-eval) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-9/08-conclusion) * [신경망 기계번역 심화 주제](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-10) * [다국어 신경망 번역](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-10/01-multilingual-nmt) * [단일 언어 코퍼스를 활용하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-10/02-monolingual-corpus) * [트랜스포머](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-10/03-transformer) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-10/04-conclusion) * [강화학습을 활용한 자연어 생성](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/01-intro) * [강화학습 기초](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/02-rl_basics) * [정책 기반 강화학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/03-policy-gradient) * [자연어 생성에 강화학습 적용하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/04-characteristic) * [강화학습을 활용한 지도학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/05-supervised-nmt) * [강화학습을 활용한 비지도학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/06-unsupervised-nmt) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-11/07-conclusion) * [듀얼리티 활용](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12) * [들어가며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12/01-intro) * [듀얼리티를 활용한 지도학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12/02-dsl) * [듀얼리티를 활용한 비지도학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12/03-dul) * [쉬어가기: Back-translation을 재해석하기](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12/04-back_translation) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-12/05-conclusion) * [NMT 시스템 구축](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-13) * [파이프라인](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-13/01-pipeline) * [구글의 NMT](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-13/02-gnmt) * [에딘버러 대학의 NMT](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-13/03-nematus) * [MS의 NMT](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-13/04-microsoft) * [전이학습](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14) * [전이학습이란?](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/01-intro) * [기존의 사전 훈련 방식](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/02-previous_work) * [ELMo](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/03-elmo) * [BERT](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/04-bert) * [GPT-2](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/05-gpt) * [XLNet](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/06-xlnet) * [마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/00-cover-14/07-conclusion) * [이 책을 마치며](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/epilogue) * [참고문헌](https://kh-kim.gitbook.io/natural-language-processing-with-pytorch/references)