[ES] Translations

[ilyaspiridonov]

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• site/es-419/agents/tutorials/0_intro_rl.ipynb
• site/es-419/guide/dtensor_overview.ipynb
• site/es-419/guide/graph_optimization.ipynb
• site/es-419/guide/sparse_tensor_guide.ipynb
• site/es-419/hub/tutorials/tf2_semantic_approximate_nearest_neighbors.ipynb
• site/es-419/hub/tutorials/tf2_text_classification.ipynb
• site/es-419/io/tutorials/avro.ipynb
• site/es-419/io/tutorials/bigtable.ipynb
• site/es-419/io/tutorials/dicom.ipynb
• site/es-419/io/tutorials/elasticsearch.ipynb
• site/es-419/io/tutorials/kafka.ipynb
• site/es-419/lattice/tutorials/aggregate_function_models.ipynb
• site/es-419/lattice/tutorials/custom_estimators.ipynb
• site/es-419/lattice/tutorials/premade_models.ipynb
• site/es-419/lattice/tutorials/shape_constraints.ipynb
• site/es-419/lite/models/convert/metadata_writer_tutorial.ipynb
• site/es-419/lite/models/modify/model_maker/image_classification.ipynb
• site/es-419/lite/models/modify/model_maker/object_detection.ipynb
• site/es-419/lite/models/modify/model_maker/question_answer.ipynb
• site/es-419/lite/models/modify/model_maker/speech_recognition.ipynb
• site/es-419/lite/models/modify/model_maker/text_classification.ipynb
• site/es-419/lite/models/modify/model_maker/text_searcher.ipynb
• site/es-419/lite/models/style_transfer/overview.ipynb
• site/es-419/lite/models/super_resolution/overview.ipynb
• site/es-419/lite/performance/post_training_float16_quant.ipynb
• site/es-419/lite/performance/post_training_integer_quant.ipynb
• site/es-419/lite/performance/post_training_integer_quant_16x8.ipynb
• site/es-419/lite/performance/post_training_quant.ipynb
• site/es-419/lite/performance/quantization_debugger.ipynb
• site/es-419/lite/tutorials/pose_classification.ipynb
• site/es-419/model_optimization/guide/clustering/clustering_comprehensive_guide.ipynb
• site/es-419/model_optimization/guide/clustering/clustering_example.ipynb
• site/es-419/model_optimization/guide/combine/cqat_example.ipynb
• site/es-419/model_optimization/guide/combine/pcqat_example.ipynb
• site/es-419/model_optimization/guide/combine/pqat_example.ipynb
• site/es-419/model_optimization/guide/combine/sparse_clustering_example.ipynb
• site/es-419/model_optimization/guide/pruning/comprehensive_guide.ipynb
• site/es-419/model_optimization/guide/pruning/pruning_for_on_device_inference.ipynb
• site/es-419/model_optimization/guide/pruning/pruning_with_keras.ipynb
• site/es-419/model_optimization/guide/pruning/pruning_with_sparsity_2_by_4.ipynb
• site/es-419/model_optimization/guide/quantization/training_comprehensive_guide.ipynb
• site/es-419/model_optimization/guide/quantization/training_example.ipynb
• site/es-419/probability/examples/A_Tour_of_TensorFlow_Probability.ipynb
• site/es-419/probability/examples/Bayesian_Gaussian_Mixture_Model.ipynb
• site/es-419/probability/examples/Bayesian_Switchpoint_Analysis.ipynb
• site/es-419/probability/examples/Distributed_Inference_with_JAX.ipynb
• site/es-419/probability/examples/Eight_Schools.ipynb
• site/es-419/probability/examples/Estimating_COVID_19_in_11_European_countries.ipynb
• site/es-419/probability/examples/FFJORD_Demo.ipynb
• site/es-419/probability/examples/Factorial_Mixture.ipynb
• site/es-419/probability/examples/Fitting_DPMM_Using_pSGLD.ipynb
• site/es-419/probability/examples/Gaussian_Copula.ipynb
• site/es-419/probability/examples/Gaussian_Process_Latent_Variable_Model.ipynb
• site/es-419/probability/examples/Generalized_Linear_Models.ipynb
• site/es-419/probability/examples/HLM_TFP_R_Stan.ipynb
• site/es-419/probability/examples/JointDistributionAutoBatched_A_Gentle_Tutorial.ipynb
• site/es-419/probability/examples/Learnable_Distributions_Zoo.ipynb
• site/es-419/probability/examples/Linear_Mixed_Effects_Model_Variational_Inference.ipynb
• site/es-419/probability/examples/Linear_Mixed_Effects_Models.ipynb
• site/es-419/probability/examples/Modeling_with_JointDistribution.ipynb
• site/es-419/probability/examples/Multilevel_Modeling_Primer.ipynb
• site/es-419/probability/examples/Multiple_changepoint_detection_and_Bayesian_model_selection.ipynb
• site/es-419/probability/examples/Optimizers_in_TensorFlow_Probability.ipynb
• site/es-419/probability/examples/Probabilistic_Layers_Regression.ipynb
• site/es-419/probability/examples/Probabilistic_Layers_VAE.ipynb
• site/es-419/probability/examples/STS_approximate_inference_for_models_with_non_Gaussian_observations.ipynb
• site/es-419/probability/examples/Structural_Time_Series_Modeling_Case_Studies_Atmospheric_CO2_and_Electricity_Demand.ipynb
• site/es-419/probability/examples/Structural_Time_Series_Modeling_Case_Studies_Atmospheric_CO2_and_Electricity_Demand_JAX.ipynb
• site/es-419/probability/examples/TFP_Release_Notebook_0_11_0.ipynb
• site/es-419/probability/examples/TFP_Release_Notebook_0_12_1.ipynb
• site/es-419/probability/examples/TFP_Release_Notebook_0_13_0.ipynb
• site/es-419/probability/examples/TensorFlow_Distributions_Tutorial.ipynb
• site/es-419/probability/examples/TensorFlow_Probability_on_JAX.ipynb
• site/es-419/probability/examples/Understanding_TensorFlow_Distributions_Shapes.ipynb
• site/es-419/probability/examples/Undocumented_Infection_and_the_Dissemination_of_SARS-CoV2.ipynb
• site/es-419/probability/examples/Variational_Inference_with_Multipart_Bijectors.ipynb
• site/es-419/quantum/tutorials/barren_plateaus.ipynb
• site/es-419/quantum/tutorials/gradients.ipynb
• site/es-419/quantum/tutorials/hello_many_worlds.ipynb
• site/es-419/quantum/tutorials/mnist.ipynb
• site/es-419/quantum/tutorials/noise.ipynb
• site/es-419/quantum/tutorials/qcnn.ipynb
• site/es-419/quantum/tutorials/quantum_data.ipynb
• site/es-419/quantum/tutorials/quantum_reinforcement_learning.ipynb
• site/es-419/quantum/tutorials/research_tools.ipynb
• site/es-419/tensorboard/dataframe_api.ipynb
• site/es-419/tensorboard/get_started.ipynb
• site/es-419/tensorboard/graphs.ipynb
• site/es-419/tensorboard/hyperparameter_tuning_with_hparams.ipynb
• site/es-419/tensorboard/image_summaries.ipynb
• site/es-419/tensorboard/migrate.ipynb
• site/es-419/tensorboard/scalars_and_keras.ipynb
• site/es-419/tensorboard/tbdev_getting_started.ipynb
• site/es-419/tensorboard/tensorboard_in_notebooks.ipynb
• site/es-419/tensorboard/tensorboard_profiling_keras.ipynb
• site/es-419/tensorboard/tensorboard_projector_plugin.ipynb
• site/es-419/tensorboard/text_summaries.ipynb
• site/es-419/tfx/tutorials/tfx/penguin_transform.ipynb
• site/es-419/tfx/tutorials/tfx/template_beam.ipynb
• site/es-419/tfx/tutorials/transform/census.ipynb
• site/es-419/tfx/tutorials/transform/simple.ipynb
• site/es-419/tutorials/interpretability/integrated_gradients.ipynb

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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

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