[KO] Translations

[ilyaspiridonov]

Translated by Alconost

[github-actions]

Localization

Translators and reviewers are encouraged to submit pull requests from our GitLocalize project.

Preview

Preview and run these notebook edits with Google Colab:

• site/ko/datasets/overview.ipynb
• site/ko/federated/tutorials/custom_aggregators.ipynb
• site/ko/federated/tutorials/custom_federated_algorithms_2.ipynb
• site/ko/federated/tutorials/federated_learning_for_image_classification.ipynb
• site/ko/federated/tutorials/federated_learning_for_text_generation.ipynb
• site/ko/federated/tutorials/federated_learning_with_differential_privacy.ipynb
• site/ko/federated/tutorials/federated_select.ipynb
• site/ko/federated/tutorials/private_heavy_hitters.ipynb
• site/ko/federated/tutorials/simulations_with_accelerators.ipynb
• site/ko/federated/tutorials/sparse_federated_learning.ipynb
• site/ko/federated/tutorials/tff_for_federated_learning_research_compression.ipynb
• site/ko/federated/tutorials/tuning_recommended_aggregators.ipynb
• site/ko/federated/tutorials/working_with_client_data.ipynb
• site/ko/guide/basics.ipynb
• site/ko/guide/core/distribution.ipynb
• site/ko/guide/dtensor_overview.ipynb
• site/ko/guide/intro_to_graphs.ipynb
• site/ko/guide/intro_to_modules.ipynb
• site/ko/guide/migrate/early_stopping.ipynb
• site/ko/guide/migrate/migrating_feature_columns.ipynb
• site/ko/guide/migrate/saved_model.ipynb
• site/ko/guide/migrate/tensorboard.ipynb
• site/ko/guide/migrate/tflite.ipynb
• site/ko/hub/tutorials/action_recognition_with_tf_hub.ipynb
• site/ko/hub/tutorials/bangla_article_classifier.ipynb
• site/ko/hub/tutorials/bert_experts.ipynb
• site/ko/hub/tutorials/bigbigan_with_tf_hub.ipynb
• site/ko/hub/tutorials/biggan_generation_with_tf_hub.ipynb
• site/ko/hub/tutorials/boundless.ipynb
• site/ko/hub/tutorials/cord_19_embeddings.ipynb
• site/ko/hub/tutorials/cord_19_embeddings_keras.ipynb
• site/ko/hub/tutorials/cropnet_cassava.ipynb
• site/ko/hub/tutorials/cropnet_on_device.ipynb
• site/ko/hub/tutorials/cross_lingual_similarity_with_tf_hub_multilingual_universal_encoder.ipynb
• site/ko/hub/tutorials/hrnet_semantic_segmentation.ipynb
• site/ko/hub/tutorials/image_classification.ipynb
• site/ko/hub/tutorials/image_enhancing.ipynb
• site/ko/hub/tutorials/image_feature_vector.ipynb
• site/ko/hub/tutorials/movenet.ipynb
• site/ko/hub/tutorials/movinet.ipynb
• site/ko/hub/tutorials/object_detection.ipynb
• site/ko/hub/tutorials/s3gan_generation_with_tf_hub.ipynb
• site/ko/hub/tutorials/semantic_approximate_nearest_neighbors.ipynb
• site/ko/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb
• site/ko/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder_lite.ipynb
• site/ko/hub/tutorials/senteval_for_universal_sentence_encoder_cmlm.ipynb
• site/ko/hub/tutorials/spice.ipynb
• site/ko/hub/tutorials/text_classification_with_tf_hub_on_kaggle.ipynb
• site/ko/hub/tutorials/text_to_video_retrieval_with_s3d_milnce.ipynb
• site/ko/hub/tutorials/tf2_arbitrary_image_stylization.ipynb
• site/ko/hub/tutorials/tf2_image_retraining.ipynb
• site/ko/hub/tutorials/tf2_object_detection.ipynb
• site/ko/hub/tutorials/tf2_semantic_approximate_nearest_neighbors.ipynb
• site/ko/hub/tutorials/tf2_text_classification.ipynb
• site/ko/hub/tutorials/tf_hub_delf_module.ipynb
• site/ko/hub/tutorials/tf_hub_film_example.ipynb
• site/ko/hub/tutorials/tf_hub_generative_image_module.ipynb
• site/ko/hub/tutorials/tweening_conv3d.ipynb
• site/ko/hub/tutorials/wav2vec2_saved_model_finetuning.ipynb
• site/ko/hub/tutorials/wiki40b_lm.ipynb
• site/ko/hub/tutorials/yamnet.ipynb
• site/ko/io/tutorials/audio.ipynb
• site/ko/model_optimization/guide/combine/pcqat_example.ipynb
• site/ko/model_optimization/guide/combine/pqat_example.ipynb
• site/ko/model_optimization/guide/combine/sparse_clustering_example.ipynb
• site/ko/model_optimization/guide/pruning/pruning_for_on_device_inference.ipynb
• site/ko/model_optimization/guide/pruning/pruning_with_sparsity_2_by_4.ipynb
• site/ko/model_optimization/guide/quantization/training_comprehensive_guide.ipynb
• site/ko/probability/examples/Generalized_Linear_Models.ipynb
• site/ko/probability/examples/HLM_TFP_R_Stan.ipynb
• site/ko/probability/examples/Multiple_changepoint_detection_and_Bayesian_model_selection.ipynb
• site/ko/probability/examples/Optimizers_in_TensorFlow_Probability.ipynb
• site/ko/probability/examples/Probabilistic_Layers_VAE.ipynb
• site/ko/probability/examples/TFP_Release_Notebook_0_11_0.ipynb
• site/ko/probability/examples/Variational_Inference_with_Multipart_Bijectors.ipynb
• site/ko/tfx/tutorials/tfx/CSV_Downloader_Component.ipynb
• site/ko/tfx/tutorials/tfx/neural_structured_learning.ipynb
• site/ko/tfx/tutorials/tfx/penguin_transform.ipynb
• site/ko/tfx/tutorials/tfx/template.ipynb
• site/ko/tfx/tutorials/tfx/template_beam.ipynb
• site/ko/tutorials/audio/simple_audio.ipynb
• site/ko/tutorials/distribute/dtensor_ml_tutorial.ipynb
• site/ko/tutorials/distribute/input.ipynb
• site/ko/tutorials/distribute/multi_worker_with_ctl.ipynb
• site/ko/tutorials/generative/autoencoder.ipynb
• site/ko/tutorials/quickstart/advanced.ipynb
• site/ko/tutorials/structured_data/time_series.ipynb
• site/ko/tutorials/video/video_classification.ipynb

Rendered notebook diffs available on ReviewNB.com.

Format and style

Use the TensorFlow docs notebook tools to format for consistent source diffs and lint for style:

$ python3 -m pip install -U --user git+https://github.com/tensorflow/docs

$ python3 -m tensorflow_docs.tools.nbfmt notebook.ipynb

$ python3 -m tensorflow_docs.tools.nblint --arg=repo:tensorflow/docs-l10n \ 
    --styles=tensorflow,tensorflow_docs_l10n notebook.ipynb

If commits are added to the pull request, synchronize your local branch: git pull origin c5d5687b16e343685e95bd704f38c63dfb1ea2d9