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| Preview and run these notebook edits with Google Colab: Notebook diffs available on ReviewNB.com. |
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Modify text_classification_rnn.ipynb and translation is complete
Choiuijin1125 left a comment
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Thank you for a great contribution :)
| " \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/en/tutorials/text/text_classification_rnn.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003e깃허브(GitHub)소스 보기\u003c/a\u003e\n", | ||
| " \u003c/td\u003e\n", | ||
| " \u003ctd\u003e\n", | ||
| " \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/docs/site/en/tutorials/text/text_classification_rnn.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003e노트북에 다운로드\u003c/a\u003e\n", |
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en/tutorials → ko/tutorials
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Is it supported to download notebook file on korean translation?
| "sample_string = 'Hello TensorFlow.'\n", | ||
| "\n", | ||
| "encoded_string = encoder.encode(sample_string)\n", | ||
| "print ('인코딩된 문자열은 {}'.format(encoded_string))\n", |
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Why don't you del postposition '은' ? just for consistency such as
인코딩된 문자열
원본 문자열
| "id": "GlYWqhTVlUyQ" | ||
| }, | ||
| "source": [ | ||
| "## 학습을 위한 데이터 준비" |
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We mostly distinguish between training and learning so I suggest
'학습을 위한 데이터 준비' → '훈련을 위한 데이터 준비'
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", |
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Please add declaration :) you can refer the other Ko document
'Note: 이 문서는 텐서플로 커뮤니티에서 번역했습니다. ...`
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I think it's not an original declaration, this is the original declaration can u change it?
Note: 이 문서는 텐서플로 커뮤니티에서 번역했습니다. 커뮤니티 번역 활동의 특성상 정확한 번역과 최신 내용을 반영하기 위해 노력함에도 불구하고 공식 영문 문서의 내용과 일치하지 않을 수 있습니다. 이 번역에 개선할 부분이 있다면 tensorflow/docs 깃헙 저장소로 풀 리퀘스트를 보내주시기 바랍니다. 문서 번역이나 리뷰에 참여하려면 docs-ko@tensorflow.org로 메일을 보내주시기 바랍니다.
| "\n", | ||
| "순환 인공 신경망(RNN)은 요소를 반복하여 시퀀스 입력을 처리합니다. RNN은 출력을 한 단계에서 입력으로 전달한 다음에 다음 단계로 전달합니다.\n", | ||
| "\n", | ||
| "`tf.keras.layers.Bidirectional` 래퍼도 RNN 레이어와 함께 사용할 수 있습니다. 이는 RNN 계층을 통해 입력을 앞뒤로 전파 한 다음 출력을 연결합니다. 이것은 RNN이 장거리 종속성을 학습하는데 도움을 줍니다." |
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I'm not sure but I think it's more fit 장기(long-term) than 장거리
Just consider my option, thanks :)
| "id": "zIwH3nto596k" | ||
| }, | ||
| "source": [ | ||
| "## 모델 학습하기" |
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For the same reason '학습하기' 훈련하기'
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modify complete
two files
| check please.. |
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@Ahnseokchan So for the late reply, I can check it regularly since now thanks :)
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", |
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I think it's not an original declaration, this is the original declaration can u change it?
Note: 이 문서는 텐서플로 커뮤니티에서 번역했습니다. 커뮤니티 번역 활동의 특성상 정확한 번역과 최신 내용을 반영하기 위해 노력함에도 불구하고 공식 영문 문서의 내용과 일치하지 않을 수 있습니다. 이 번역에 개선할 부분이 있다면 tensorflow/docs 깃헙 저장소로 풀 리퀘스트를 보내주시기 바랍니다. 문서 번역이나 리뷰에 참여하려면 docs-ko@tensorflow.org로 메일을 보내주시기 바랍니다.
| "source": [ | ||
| "[GRU layers](https://www.tensorflow.org/api_docs/python/tf/keras/layers/GRU)과 같은 기존의 다른 반복 계층을 확인합니다..\n", | ||
| "\n", | ||
| "만약 custom RNN 빌드에 관심이 있으시다면, [Keras RNN Guide](../../guide/keras/rnn.ipynb)를 보길 바랍니다..\n" |
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We can translate 'custom' as '사용자 정의', So I suggest '사용자 정의 RNN' or '사용자 정의 순환신경망' and '케라스 순환신경망 가이드'
| "id": "DwSE_386uhxD" | ||
| }, | ||
| "source": [ | ||
| "위의 모델은 시퀀스에 적용된 패딩을 가리지 않습니다. 패딩 된 시퀀스를 학습하고 패딩되지 않은 시퀀스를 테스트하면 왜곡이 일어날 수 있습니다. 이상적으로 이를 피하기 위하여 [마스킹을 사용](../../guide/keras/masking_and_padding)하지만 아래에서 볼 수 있듯이 출력에는 약간의 영향만 미칩니다.\n", |
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[마스킹을 사용] → [마스킹]을 사용 :)
| "id": "lUWearf0Gw-p" | ||
| }, | ||
| "source": [ | ||
| "Note: 이 문서는 텐서플로 커뮤니티에서 번역했습니다. 이 번역에 개선할 부분이 있다면 tensorflow/docs 깃헙 저장소로 풀 리퀘스트를 보내주시기 바랍니다. 텍스트 분류 튜토리얼은 감정 분석을 위한 [IMDB 대형 영화 리뷰 데이터셋](http://ai.stanford.edu/~amaas/data/sentiment/)에서 [순환 인공신경망](https://developers.google.com/machine-learning/glossary/#recurrent_neural_network)을 훈련시킵니다." |
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We mostly translate 'RNN' as '순환신경망' so I suggest '순환신경망'
| "\n", | ||
| "이 인덱스-조회는 one-hot 인코딩 된 벡터를 `tf.keras.layers.Dense` 레이어를 통해 전달하는 작업보다 훨씬 효율적입니다.\n", | ||
| "\n", | ||
| "순환 인공 신경망(RNN)은 요소를 반복하여 시퀀스 입력을 처리합니다. RNN은 출력을 한 단계에서 입력으로 전달한 다음에 다음 단계로 전달합니다.\n", |
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'순환 인공 신경망' → '순환신경망' :)
| @lamberta Hi billy.. :), this PR is LGTM. |
| " \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/text/text_classification_rnn\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eTensorFlow에서 보기\u003c/a\u003e\n", | ||
| " \u003c/td\u003e\n", | ||
| " \u003ctd\u003e\n", | ||
| " \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/text/text_classification_rnn.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003e구글 코랩(Colab)에서 실행하기\u003c/a\u003e\n", |
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| " \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/text/text_classification_rnn.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003e구글 코랩(Colab)에서 실행하기\u003c/a\u003e\n", | |
| " \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/ko/tutorials/text/text_classification_rnn.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003e구글 코랩(Colab)에서 실행하기\u003c/a\u003e\n", |
Point to Korean notebook :)
| "id": "UQK2Na3Z_aMx" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ |
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Remove empty code cell at the end
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "train_dataset = train_dataset.shuffle(BUFFER_SIZE)\n", |
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Notebook is throwing an error:
AttributeError: 'ShuffleDataset' object has no attribute 'output_shapes'
Can you double-check this notebook against the one in en/ ? Thanks
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Hi Billy, Oh, it's because of the version issue. can you close this PR? I'll make new PR for this document(there is no response from a translator.. :))
| Thanks for the submission. Closing for @Choiuijin1125 to resolve remaining issues. Thanks |
translate text_classification_rnn.ipynb
EN -> KO
EN : https://github.com/tensorflow/docs/blob/master/site/en/tutorials/text/text_classification_rnn.ipynb