[PT-BR] Translations

[ilyaspiridonov]

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Preview and run these notebook edits with Google Colab:

• site/pt-br/guide/core/distribution.ipynb
• site/pt-br/guide/core/matrix_core.ipynb
• site/pt-br/guide/core/mlp_core.ipynb
• site/pt-br/guide/core/quickstart_core.ipynb
• site/pt-br/guide/migrate/migrating_feature_columns.ipynb
• site/pt-br/guide/saved_model.ipynb
• site/pt-br/guide/tpu.ipynb
• site/pt-br/lite/guide/signatures.ipynb
• site/pt-br/lite/models/convert/metadata_writer_tutorial.ipynb
• site/pt-br/lite/models/modify/model_maker/audio_classification.ipynb
• site/pt-br/lite/models/modify/model_maker/image_classification.ipynb
• site/pt-br/lite/models/modify/model_maker/object_detection.ipynb
• site/pt-br/lite/models/modify/model_maker/question_answer.ipynb
• site/pt-br/lite/models/modify/model_maker/speech_recognition.ipynb
• site/pt-br/lite/models/modify/model_maker/text_classification.ipynb
• site/pt-br/lite/models/modify/model_maker/text_searcher.ipynb
• site/pt-br/neural_structured_learning/tutorials/adversarial_keras_cnn_mnist.ipynb
• site/pt-br/neural_structured_learning/tutorials/graph_keras_lstm_imdb.ipynb
• site/pt-br/neural_structured_learning/tutorials/graph_keras_mlp_cora.ipynb
• site/pt-br/probability/examples/A_Tour_of_TensorFlow_Probability.ipynb
• site/pt-br/probability/examples/Bayesian_Gaussian_Mixture_Model.ipynb
• site/pt-br/probability/examples/Bayesian_Switchpoint_Analysis.ipynb
• site/pt-br/probability/examples/Distributed_Inference_with_JAX.ipynb
• site/pt-br/probability/examples/Eight_Schools.ipynb
• site/pt-br/probability/examples/Estimating_COVID_19_in_11_European_countries.ipynb
• site/pt-br/probability/examples/FFJORD_Demo.ipynb
• site/pt-br/probability/examples/Factorial_Mixture.ipynb
• site/pt-br/probability/examples/Fitting_DPMM_Using_pSGLD.ipynb
• site/pt-br/probability/examples/Gaussian_Copula.ipynb
• site/pt-br/probability/examples/Gaussian_Process_Latent_Variable_Model.ipynb
• site/pt-br/probability/examples/Generalized_Linear_Models.ipynb
• site/pt-br/probability/examples/HLM_TFP_R_Stan.ipynb
• site/pt-br/probability/examples/JointDistributionAutoBatched_A_Gentle_Tutorial.ipynb
• site/pt-br/probability/examples/Learnable_Distributions_Zoo.ipynb
• site/pt-br/probability/examples/Linear_Mixed_Effects_Model_Variational_Inference.ipynb
• site/pt-br/probability/examples/Linear_Mixed_Effects_Models.ipynb
• site/pt-br/probability/examples/Modeling_with_JointDistribution.ipynb
• site/pt-br/probability/examples/Multilevel_Modeling_Primer.ipynb
• site/pt-br/quantum/tutorials/barren_plateaus.ipynb
• site/pt-br/quantum/tutorials/gradients.ipynb
• site/pt-br/quantum/tutorials/hello_many_worlds.ipynb
• site/pt-br/quantum/tutorials/mnist.ipynb
• site/pt-br/quantum/tutorials/noise.ipynb
• site/pt-br/quantum/tutorials/qcnn.ipynb
• site/pt-br/quantum/tutorials/quantum_data.ipynb
• site/pt-br/tensorboard/dataframe_api.ipynb
• site/pt-br/tensorboard/get_started.ipynb
• site/pt-br/tensorboard/graphs.ipynb
• site/pt-br/tensorboard/hyperparameter_tuning_with_hparams.ipynb
• site/pt-br/tensorboard/image_summaries.ipynb
• site/pt-br/tensorboard/migrate.ipynb
• site/pt-br/tensorboard/scalars_and_keras.ipynb
• site/pt-br/tensorboard/tbdev_getting_started.ipynb
• site/pt-br/tensorboard/tensorboard_in_notebooks.ipynb
• site/pt-br/tensorboard/tensorboard_profiling_keras.ipynb
• site/pt-br/tensorboard/tensorboard_projector_plugin.ipynb
• site/pt-br/tensorboard/text_summaries.ipynb
• site/pt-br/tfx/tutorials/data_validation/tfdv_basic.ipynb
• site/pt-br/tfx/tutorials/mlmd/mlmd_tutorial.ipynb
• site/pt-br/tfx/tutorials/model_analysis/tfma_basic.ipynb
• site/pt-br/tfx/tutorials/serving/rest_simple.ipynb
• site/pt-br/tfx/tutorials/tfx/CSV_Downloader_Component.ipynb
• site/pt-br/tfx/tutorials/tfx/components.ipynb
• site/pt-br/tfx/tutorials/tfx/components_keras.ipynb
• site/pt-br/tfx/tutorials/tfx/gcp/vertex_pipelines_bq.ipynb
• site/pt-br/tfx/tutorials/tfx/gcp/vertex_pipelines_simple.ipynb
• site/pt-br/tfx/tutorials/tfx/gcp/vertex_pipelines_vertex_training.ipynb
• site/pt-br/tfx/tutorials/tfx/neural_structured_learning.ipynb
• site/pt-br/tfx/tutorials/tfx/penguin_simple.ipynb
• site/pt-br/tfx/tutorials/tfx/penguin_template.ipynb
• site/pt-br/tfx/tutorials/tfx/penguin_tfdv.ipynb
• site/pt-br/tfx/tutorials/tfx/penguin_tfma.ipynb
• site/pt-br/tfx/tutorials/tfx/penguin_transform.ipynb
• site/pt-br/tfx/tutorials/tfx/python_function_component.ipynb
• site/pt-br/tfx/tutorials/tfx/recommenders.ipynb
• site/pt-br/tfx/tutorials/tfx/template.ipynb
• site/pt-br/tfx/tutorials/tfx/template_beam.ipynb
• site/pt-br/tfx/tutorials/transform/census.ipynb
• site/pt-br/tfx/tutorials/transform/simple.ipynb
• site/pt-br/tutorials/images/transfer_learning.ipynb
• site/pt-br/tutorials/quickstart/advanced.ipynb
• site/pt-br/tutorials/quickstart/beginner.ipynb
• site/pt-br/tutorials/video/video_classification.ipynb
• site/pt-br/xla/tutorials/autoclustering_xla.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 7807687baa904a9456719e790d6ea546dcad0bc6

[ilyaspiridonov]

@pcoet Apart from the standard license errors, there are a couple of files that also throw "Malformed links" errors - and those are inherited from the English counterparts (i.e. links are missing in the original files).
Otherwise should be good.

[ilyaspiridonov]

@pcoet