This page contains code samples for Vertex AI. To search and filter code samples for other Google Cloud products, see the Google Cloud sample browser.
Cancel a hyperparameter tuning job
Cancels a hyperparameter tuning job using the cancel_hyperparameter_tuning_job method.
Create a batch prediction job
Creates a batch prediction job using the create_batch_prediction_job method.
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Create a batch prediction job for BigQuery
Creates a batch prediction job for BigQuery using the create_batch_prediction_job method.
Create a batch prediction job for tabular forecasting
Creates a batch prediction job for tabular forecasting using the create_batch_prediction_job method.
Create a batch prediction job for text classification
Creates a batch prediction job for text classification using the create_batch_prediction_job method.
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Create a batch prediction job for text entity extraction
Creates a batch prediction job for text entity extraction using the create_batch_prediction_job method.
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Create a batch prediction job for text sentiment analysis
Creates a batch prediction job for text sentiment analysis using the create_batch_prediction_job method.
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Create a batch prediction job for video action recognition
Creates a batch prediction job for video action recognition using the create_batch_prediction_job method.
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Create a batch prediction job for video classification
Creates a batch prediction job for video classification using the create_batch_prediction_job method.
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Create a batch prediction job for video object tracking
Creates a batch prediction job for video object tracking using the create_batch_prediction_job method.
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Create a data labeling job
Creates a data labeling job using the create_data_labeling_job method.
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Create a data labeling job for image segmentation
Creates a data labeling job for image segmentation using the create_data_labeling_job method.
Create a data labeling job for images
Creates a data labeling job for images using the create_data_labeling_job method.
Create a dataset for image
Creates a dataset for image using the create_dataset method.
Create a dataset for tabular BigQuery
Creates a dataset for tabular BigQuery using the create_dataset method.
Create a dataset for tabular Cloud Storage
Creates a dataset for tabular Cloud Storage using the create_dataset method.
Create a dataset for text
Creates a dataset for text using the create_dataset method.
Create a dataset for video
Creates a dataset for video using the create_dataset method.
Create a hyperparameter tuning job for python package
Creates a hyperparameter tuning job for python package using the create_hyperparameter_tuning_job method.
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Create a training pipeline for custom job
Creates a training pipeline for custom job using the create_training_pipeline method.
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Create a training pipeline for image classification
Creates a training pipeline for image classification using the create_training_pipeline method.
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Create a training pipeline for image object detection
Creates a training pipeline for image object detection using the create_training_pipeline method.
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Create a training pipeline for tabular classification
Creates a training pipeline for tabular classification using the create_training_pipeline method.
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Create a training pipeline for tabular forecasting
Creates a training pipeline for tabular forecasting using the create_training_pipeline method.
Create a training pipeline for tabular regression
Creates a training pipeline for tabular regression using the create_training_pipeline method.
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Create a training pipeline for text classification
Creates a training pipeline for text classification using the create_training_pipeline method.
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Create a training pipeline for text entity extraction
Creates a training pipeline for text entity extraction using the create_training_pipeline method.
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Create a training pipeline for text sentiment analysis
Creates a training pipeline for text sentiment analysis using the create_training_pipeline method.
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Create a training pipeline for video action recognition
Creates a training pipeline for video action recognition using the create_training_pipeline method.
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Create a training pipeline for video classification
Creates a training pipeline for video classification using the create_training_pipeline method.
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Create a training pipeline for video object tracking
Creates a training pipeline for video object tracking using the create_training_pipeline method.
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Create an endpoint
Creates an endpoint using the create_endpoint method.
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- Get online predictions and explanations
- Get predictions from a custom trained model
- Get predictions from a image classification model
- Get predictions from a image object detection model
- Get predictions from a text classification model
- Get predictions from a text entity extraction model
- Get predictions from a text sentiment analysis model
- Get TabNet online predictions
- Get Wide & Deep online predictions
Delete a hyperparameter tuning job
Deletes a hyperparameter tuning job using the delete_hyperparameter_tuning_job method.
Deploy a model for custom trained model
Deploys a model for custom trained model using the deploy_model method.
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Export a model for tabular classification
Exports a model for tabular classification using the export_model method.
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Export a model for video action recognition
Exports a model for video action recognition using the export_model method.
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Get a hyperparameter tuning job
Gets a hyperparameter tuning job using the get_hyperparameter_tuning_job method.
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Get a model evaluation for image classification
Gets a model evaluation for image classification using the get_model_evaluation method.
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Get a model evaluation for image object detection
Gets a model evaluation for image object detection using the get_model_evaluation method.
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Get a model evaluation for tabular classification
Gets a model evaluation for tabular classification using the get_model_evaluation method.
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Get a model evaluation for tabular regression
Gets a model evaluation for tabular regression using the get_model_evaluation method.
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Get a model evaluation for text classification
Gets a model evaluation for text classification using the get_model_evaluation method.
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Get a model evaluation for text entity extraction
Gets a model evaluation for text entity extraction using the get_model_evaluation method.
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Get a model evaluation for text sentiment analysis
Gets a model evaluation for text sentiment analysis using the get_model_evaluation method.
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Get a model evaluation for video action recognition
Gets a model evaluation for video action recognition using the get_model_evaluation method.
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Get a model evaluation for video classification
Gets a model evaluation for video classification using the get_model_evaluation method.
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Get a model evaluation for video object tracking
Gets a model evaluation for video object tracking using the get_model_evaluation method.
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Get a model evaluation slice
Gets a model evaluation slice using the get_model_evaluation_slice method.
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- Evaluate and iterate AutoML image classification models
- Evaluate and iterate AutoML image object detection models
- Evaluate and iterate AutoML text classification models
- Evaluate and iterate AutoML text entity extraction models
- Evaluate and iterate AutoML text sentiment analysis models
- Evaluate and iterate AutoML video action recognition models
- Evaluate and iterate AutoML video classification models
- Evaluate and iterate AutoML video object tracking models
- Evaluate AutoML classification and regression models
Get a training pipeline
Gets a training pipeline using the get_training_pipeline method.
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Import data for image classification single label
Imports data for image classification single label using the import_data method.
Import data for image object detection
Imports data for image object detection using the import_data method.
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Import data for text classification single label
Imports data for text classification single label using the import_data method.
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Import data for text entity extraction
Imports data for text entity extraction using the import_data method.
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Import data for text sentiment analysis
Imports data for text sentiment analysis using the import_data method.
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Import data for video action recognition
Imports data for video action recognition using the import_data method.
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Import data for video classification
Imports data for video classification using the import_data method.
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Import data for video object tracking
Imports data for video object tracking using the import_data method.
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List model evaluation slices
Lists model evaluation slices using the list_model_evaluation_slices method.
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- Evaluate and iterate AutoML image classification models
- Evaluate and iterate AutoML image object detection models
- Evaluate and iterate AutoML text classification models
- Evaluate and iterate AutoML text entity extraction models
- Evaluate and iterate AutoML text sentiment analysis models
- Evaluate and iterate AutoML video action recognition models
- Evaluate and iterate AutoML video classification models
- Evaluate and iterate AutoML video object tracking models
- Evaluate AutoML classification and regression models
Predict for custom trained model
Gets prediction for custom trained model using the predict method.
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Predict for image object detection
Gets prediction for image object detection using the predict method.
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Predict for tabular classification
Gets prediction for tabular classification using the predict method.
Predict for tabular regression
Gets prediction for tabular regression using the predict method.
Predict for text classification single label
Gets prediction for text classification single label using the predict method.
Predict for text entity extraction
Gets prediction for text entity extraction using the predict method.
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Predict for text sentiment analysis
Gets prediction for text sentiment analysis using the predict method.
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Upload a model for explain image managed container
Uploads a model for explain image managed container using the upload_model method.
Upload a model for explain tabular managed container
Uploads a model for explain tabular managed container using the upload_model method.