Merge branch 'main' into autoreview_25

notebooks/official/automl/README.md

@@ -1,5 +1,5 @@
 
-[AutoML Tabular Training and Prediction](official/automl/automl-tabular-classification.ipynb)
+[AutoML Tabular Training and Prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl-tabular-classification.ipynb)
 
 Learn how to train and make predictions on an AutoML model based on a tabular dataset.
 
@@ -11,7 +11,7 @@ The steps performed include the following:
 - Make a prediction by sending data.
 - Undeploy the `Model` resource.
 
-[Create, train, and deploy an AutoML text classification model](official/automl/automl-text-classification.ipynb)
+[Create, train, and deploy an AutoML text classification model](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl-text-classification.ipynb)
 
 Learn how to use `AutoML` to train a text classification model.
 
@@ -25,7 +25,7 @@ The steps performed include:
 * Make an online prediction
 * Make a batch prediction
 
-[AutoML training video classification model for batch prediction](official/automl/sdk_automl_video_classification_batch.ipynb)
+[AutoML training video classification model for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_video_classification_batch.ipynb)
 
 Learn how to create an AutoML video classification model from a Python script, and then do a batch prediction using the Vertex AI SDK.
 
@@ -41,9 +41,9 @@ The steps performed include:
 
 * Batch Prediction Service: Does a queued (batch) prediction for the entire set of instances in the background and stores the results in a Cloud Storage bucket when ready.
 
-[AutoML training text entity extraction model for online prediction](official/automl/sdk_automl_text_entity_extraction_online.ipynb)
+[AutoML training text entity extraction model for online prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_text_entity_extraction_online.ipynb)
 
-Learn how to create an AutoML text entity extraction model and deploy for online prediction from a Python script using the Vertex SDK.
+In this tutorial, you how to create an AutoML text entity extraction model and deploy for online prediction from a Python script using the Vertex SDK.
 
 The steps performed include:
 
@@ -54,7 +54,7 @@ The steps performed include:
 - Make a prediction.
 - Undeploy the `Model`.
 
-[AutoML tabular forecasting model for batch prediction](official/automl/sdk_automl_tabular_forecasting_batch.ipynb)
+[AutoML tabular forecasting model for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_forecasting_batch.ipynb)
 
 Learn how to create an `AutoML` tabular forecasting model from a Python script, and then do a batch prediction using the Vertex AI SDK.
 
@@ -65,7 +65,7 @@ The steps performed include:
 - Obtain the evaluation metrics for the `Model` resource.
 - Make a batch prediction.
 
-[AutoML training image object detection model for batch prediction](official/automl/sdk_automl_image_object_detection_batch.ipynb)
+[AutoML training image object detection model for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_image_object_detection_batch.ipynb)
 
 Learn how to create an AutoML image object detection model from a Python script, and then do a batch prediction using the Vertex AI SDK.
 
@@ -81,7 +81,7 @@ The steps performed include:
 
 * Batch Prediction Service: Does a queued (batch) prediction for the entire set of instances in the background and stores the results in a Cloud Storage bucket when ready.
 
-[AutoML training video action recognition model for batch prediction](official/automl/sdk_automl_video_action_recognition_batch.ipynb)
+[AutoML training video action recognition model for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_video_action_recognition_batch.ipynb)
 
 Learn how to create an AutoML video action recognition model from a Python script, and then do a batch prediction using the Vertex AI SDK.
 
@@ -97,7 +97,7 @@ The steps performed include:
 
 * Batch Prediction Service: Does a queued (batch) prediction for the entire set of instances in the background and stores the results in a Cloud Storage bucket when ready.
 
-[AutoML Tabular Pipeline](official/automl/automl_tabular_on_vertex_pipelines.ipynb)
+[AutoML Tabular Pipeline](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl_tabular_on_vertex_pipelines.ipynb)
 
 Learn how to create two regression models using [Vertex Pipelines](https://cloud.
 
@@ -106,7 +106,7 @@ The steps performed are:
 - Create a training pipeline that reduces the search space from the default to save time.
 - Create a training pipeline that reuses the architecture search results from the previous pipeline to save time.
 
-[AutoML training text sentiment analysis model for online prediction](official/automl/sdk_automl_text_sentiment_analysis_online.ipynb)
+[AutoML training text sentiment analysis model for online prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_text_sentiment_analysis_online.ipynb)
 
 Learn how to create an AutoML text sentiment analysis model and deploy for online prediction from a Python script using the Vertex SDK.
 
@@ -119,7 +119,7 @@ The steps performed include:
 - Make a prediction.
 - Undeploy the `Model`.
 
-[Compare Vertex AI Forecasting and BigQuery ML ARIMA_PLUS](official/automl/automl_forecasting_bqml_arima_plus_comparison.ipynb)
+[Compare Vertex AI Forecasting and BigQuery ML ARIMA_PLUS](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl_forecasting_bqml_arima_plus_comparison.ipynb)
 
 Learn how to create an BQML ARIMA_PLUS model using a training [Vertex AI Pipeline](https://cloud.
 
@@ -134,7 +134,7 @@ The steps performed are:
 - Make a batch prediction with the Model.
 
 
-[AutoML training tabular regression model for online prediction using BigQuery](official/automl/sdk_automl_tabular_regression_online_bq.ipynb)
+[AutoML training tabular regression model for online prediction using BigQuery](https://github.com/GoogleCloudPlatform/vertex-ai-samples/tree/master/notebooks/official/automl/sdk_automl_tabular_regression_online_bq.ipynb)
 
 Learn how to create an AutoML tabular regression model and deploy for online prediction from a Python script using the Vertex AI SDK.
 
@@ -147,7 +147,7 @@ The steps performed include:
 - Make a prediction.
 - Undeploy the `Model`.
 
-[AutoML training video object tracking model for batch prediction](official/automl/sdk_automl_video_object_tracking_batch.ipynb)
+[AutoML training video object tracking model for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_video_object_tracking_batch.ipynb)
 
 Learn how to create an AutoML video object tracking model from a Python script, and then do a batch prediction using the Vertex SDK.
 
@@ -163,7 +163,7 @@ The steps performed include:
 
 * Batch Prediction Service: Does a queued (batch) prediction for the entire set of instances in the background and stores the results in a Cloud Storage bucket when ready.
 
-[AutoML training tabular regression model for batch prediction using BigQuery](official/automl/sdk_automl_tabular_regression_batch_bq.ipynb)
+[AutoML training tabular regression model for batch prediction using BigQuery](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_batch_bq.ipynb)
 
 Learn how to create an AutoML tabular regression model and deploy it for batch prediction using the Vertex AI SDK for Python.
 

notebooks/official/bigquery_ml/README.md

@@ -1,5 +1,5 @@
 
-[Online prediction with BigQuery ML](official/bigquery_ml/bqml-online-prediction.ipynb)
+[Online prediction with BigQuery ML](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/bigquery_ml/bqml-online-prediction.ipynb)
 
 Learn how to train and deploy a churn prediction model for real-time inference, with the data in BigQuery and model trained using BigQuery ML, registered to Vertex AI Model Registry, and deployed to an endpoint on Vertex AI for online predictions.
 

notebooks/official/custom/README.md

@@ -1,5 +1,5 @@
 
-[Custom training and batch prediction](official/custom/sdk-custom-image-classification-batch.ipynb)
+[Custom training and batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/custom/sdk-custom-image-classification-batch.ipynb)
 
 Learn to use `Vertex AI Training` to create a custom trained model and use `Vertex AI Batch Prediction` to do a batch prediction on the trained model.
 
@@ -9,7 +9,7 @@ The steps performed include:
 - Upload the trained model artifacts as a `Model` resource.
 - Make a batch prediction.
 
-[Profile model training performance using Profiler](official/custom/custom_training_tensorboard_profiler.ipynb)
+[Profile model training performance using Profiler](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/custom/custom_training_tensorboard_profiler.ipynb)
 
 Learn how to enable Vertex AI TensorBoard Profiler for custom training jobs.
 
@@ -21,7 +21,7 @@ The steps performed include:
 - View the TensorBoard Profiler dashboard
 
 
-[Training a TensorFlow model on BigQuery data](official/custom/custom-tabular-bq-managed-dataset.ipynb)
+[Training a TensorFlow model on BigQuery data](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/custom/custom-tabular-bq-managed-dataset.ipynb)
 
 Learn how to create a custom-trained model from a Python script in a Docker container using the Vertex AI SDK for Python, and then get a prediction from the deployed model by sending data.
 
@@ -33,7 +33,7 @@ The steps performed include:
 - Make a prediction.
 - Undeploy the `Model` resource.
 
-[Custom training and online prediction](official/custom/sdk-custom-image-classification-online.ipynb)
+[Custom training and online prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/custom/sdk-custom-image-classification-online.ipynb)
 
 Learn to use `Vertex AI Training` to create a custom-trained model from a Python script in a Docker container, and learn to use `Vertex AI Prediction` to do a prediction on the deployed model by sending data.
 
@@ -46,7 +46,7 @@ The steps performed include:
 - Make a prediction.
 - Undeploy the `Model` resource.
 
-[Deploying Iris-detection model using FastAPI and Vertex AI custom container serving](official/custom/SDK_Custom_Container_Prediction.ipynb)
+[Deploying Iris-detection model using FastAPI and Vertex AI custom container serving](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/custom/SDK_Custom_Container_Prediction.ipynb)
 
 Learn how to create, deploy and serve a custom classification model on Vertex AI.
 

notebooks/official/experiments/README.md

@@ -1,11 +1,11 @@
 
-[Compare pipeline runs with Vertex AI Experiments](official/experiments/comparing_pipeline_runs.ipynb)
+[Compare pipeline runs with Vertex AI Experiments](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/comparing_pipeline_runs.ipynb)
 
 Learn how to use `Vertex AI Experiments` to log a pipeline job and compare different pipeline jobs.
 
 
 
-[Track parameters and metrics for locally trained models](official/experiments/comparing_local_trained_models.ipynb)
+[Track parameters and metrics for locally trained models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/comparing_local_trained_models.ipynb)
 
 Learn how to use Vertex AI Experiments to compare and evaluate model experiments.
 
@@ -16,7 +16,7 @@ The steps performed include:
 - log the evaluation metrics
 
 
-[Build Vertex AI Experiment lineage for custom training](official/experiments/build_model_experimentation_lineage_with_prebuild_code.ipynb)
+[Build Vertex AI Experiment lineage for custom training](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/build_model_experimentation_lineage_with_prebuild_code.ipynb)
 
 Learn how to integrate preprocessing code in a Vertex AI experiments.
 

notebooks/official/explainable_ai/README.md

@@ -1,7 +1,7 @@
 
-[Custom training tabular regression model for batch prediction with explainabilty](official/explainable_ai/sdk_custom_tabular_regression_batch_explain.ipynb)
+[Custom training tabular regression model for batch prediction with explainabilty](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_custom_tabular_regression_batch_explain.ipynb)
 
-Learn how to use `Vertex AI Training and Explainable AI` to create a custom image classification model with explanations, and then you learn to use `Vertex AI Batch Prediction` to make a batch prediction request with explanations.
+In this tutorial, you how learn to use `Vertex AI Training and Explainable AI` to create a custom image classification model with explanations, and then you learn to use `Vertex AI Batch Prediction` to make a batch prediction request with explanations.
 
 The steps performed include:
 
@@ -11,7 +11,7 @@ The steps performed include:
 - Upload the trained model artifacts and explanations as a `Model` resource.
 - Make a batch prediction with explanations.
 
-[AutoML training tabular binary classification model for batch explanation](official/explainable_ai/sdk_automl_tabular_binary_classification_batch_explain.ipynb)
+[AutoML training tabular binary classification model for batch explanation](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_automl_tabular_binary_classification_batch_explain.ipynb)
 
 Learn to use `AutoML` to create a tabular binary classification model from a Python script, and then learn to use `Vertex AI Batch Prediction` to make predictions with explanations.
 
@@ -27,9 +27,9 @@ The steps performed include:
 
 * Batch Prediction Service: Does a queued (batch) prediction for the entire set of instances in the background and stores the results in a Cloud Storage bucket when ready.
 
-[AutoML training tabular classification model for online explanation](official/explainable_ai/sdk_automl_tabular_classification_online_explain.ipynb)
+[AutoML training tabular classification model for online explanation](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_automl_tabular_classification_online_explain.ipynb)
 
-Learn how to use `AutoML` to create a tabular binary classification model from a Python script, and then learn to use `Vertex AI Online Prediction` to make online predictions with explanations.
+In this tutorial, you how to learn to use `AutoML` to create a tabular binary classification model from a Python script, and then learn to use `Vertex AI Online Prediction` to make online predictions with explanations.
 
 The steps performed include:
 
@@ -41,7 +41,7 @@ The steps performed include:
 - Make an online prediction request with explainability.
 - Undeploy the `Model` resource.
 
-[Custom training image classification model for online prediction with explainabilty](official/explainable_ai/sdk_custom_image_classification_online_explain.ipynb)
+[Custom training image classification model for online prediction with explainabilty](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_custom_image_classification_online_explain.ipynb)
 
 Learn how to use `Vertex AI Training and Explainable AI` to create a custom image classification model with explanations, and then you learn to use `Vertex AI Prediction` to make an online prediction request with explanations.
 
@@ -56,7 +56,7 @@ The steps performed include:
 - Make a prediction with explanation.
 - Undeploy the `Model` resource.
 
-[Custom training tabular regression model for online prediction with explainabilty using get_metadata](official/explainable_ai/sdk_custom_tabular_regression_online_explain_get_metadata.ipynb)
+[Custom training tabular regression model for online prediction with explainabilty using get_metadata](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_custom_tabular_regression_online_explain_get_metadata.ipynb)
 
 Learn how to create a custom model from a Python script in a Google prebuilt Docker container using the Vertex SDK, and then do a prediction with explanations on the deployed model by sending data.
 
@@ -72,7 +72,7 @@ The steps performed include:
 - Make a prediction with explanation.
 - Undeploy the `Model` resource.
 
-[Custom training image classification model for batch prediction with explainabilty](official/explainable_ai/sdk_custom_image_classification_batch_explain.ipynb)
+[Custom training image classification model for batch prediction with explainabilty](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/explainable_ai/sdk_custom_image_classification_batch_explain.ipynb)
 
 Learn to use `Vertex AI Training and Explainable AI` to create a custom image classification model with explanations, and then you learn to use `Vertex AI Batch Prediction` to make a batch prediction request with explanations.