fix: restore requirements.txt

notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/t5x_base_optimized_online_prediction.ipynb

@@ -40,18 +40,18 @@
       "source": [
         "<table align=\"left\">\n",
         "  <td>\n",
-        "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/t5x_base_optimized_online_prediction.ipynb\">\n",
+        "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/bert_optimized_online_prediction.ipynb\">\n",
         "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
         "    </a>\n",
         "  </td>\n",
         "  <td>\n",
-        "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/t5x_base_optimized_online_prediction.ipynb\">\n",
+        "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/bert_optimized_online_prediction.ipynb\">\n",
         "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
         "      View on GitHub\n",
         "    </a>\n",
         "  </td>\n",
         "  <td>\n",
-        "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/t5x_base_optimized_online_prediction.ipynb\">\n",
+        "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/community/vertex_endpoints/optimized_tensorflow_runtime/bert_optimized_online_prediction.ipynb\">\n",
         "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
         "      Open in Vertex AI Workbench\n",
         "    </a>\n",

notebooks/official/automl/README.md

@@ -14,7 +14,7 @@ The steps performed include the following:
 
 ```
 
-   Learn more about [Classification for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/overview).
+   Learn more about [Tabular classification](https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/overview).
 
 
 [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)
@@ -34,7 +34,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Classification for text data](https://cloud.google.com/vertex-ai/docs/training-overview#classification_for_text).
+   Learn more about [AutoML Text classification](https://cloud.google.com/vertex-ai/docs/text-data/classification/train-model).
 
 
 [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)
@@ -54,7 +54,9 @@ The steps performed are:
 
 ```
 
-   Learn more about [BQML ARIMA+ forecasting for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting-arima/overview).
+   Learn more about [AutoML Forecasting](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting/overview).
+
+   Learn more about [BQML Forecasting](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting-arima/overview).
 
 
 [AutoML Tabular Workflow pipelines](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl_tabular_on_vertex_pipelines.ipynb)
@@ -69,26 +71,7 @@ The steps performed are:
 
 ```
 
-   Learn more about [Tabular Workflow for E2E AutoML](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/e2e-automl).
-
-
-[Get started with AutoML Training](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/get_started_automl_training.ipynb)
-
-```
-Learn how to use `AutoML` for training with `Vertex AI`.
-
-The steps performed include:
-
-- Train an image model
-- Export the image model as an edge model
-- Train a tabular model
-- Export the tabular model as a cloud model
-- Train a text model
-- Train a video model
-
-```
-
-   Learn more about [Vertex AI for AutoML](https://cloud.google.com/vertex-ai/docs/start/automl-users).
+   Learn more about [AutoML Tabular Workflows](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/e2e-automl).
 
 
 [AutoML training hierarchical forecasting for batch prediction](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_forecasting_hierarchical_batch.ipynb)
@@ -107,7 +90,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Hierarchical forecasting for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting/hierarchical).
+   Learn more about [AutoML Forecasting](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting/overview).
 
 
 [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)
@@ -124,7 +107,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Object detection for image data](https://cloud.google.com/vertex-ai/docs/training-overview#object_detection_for_images).
+   Learn more about [AutoML Image](https://cloud.google.com/vertex-ai/docs/image-data/object-detection/train-model).
 
 
 [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)
@@ -141,7 +124,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Forecasting for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting/overview).
+   Learn more about [AutoML Forecasting](https://cloud.google.com/vertex-ai/docs/tabular-data/forecasting/tutorials-samples).
 
 
 [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)
@@ -160,7 +143,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Regression for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/overview).
+   Learn more about [AutoML Tabular](https://cloud.google.com/vertex-ai/docs/training-overview#tabular_data).
 
 
 [AutoML training tabular regression model for online prediction using BigQuery](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_online_bq.ipynb)
@@ -179,7 +162,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Regression for tabular data](https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/overview).
+   Learn more about [AutoML Tabular](https://cloud.google.com/vertex-ai/docs/training-overview#tabular_data).
 
 
 [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)
@@ -198,7 +181,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Entity extraction for text data](https://cloud.google.com/vertex-ai/docs/training-overview#entity_extraction_for_text).
+   Learn more about [AutoML Text](https://cloud.google.com/vertex-ai/docs/text-data/entity-extraction/train-model).
 
 
 [Training an AutoML text sentiment analysis model for online predictions](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_text_sentiment_analysis_online.ipynb)
@@ -218,7 +201,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Sentiment analysis for text data](https://cloud.google.com/vertex-ai/docs/training-overview#sentiment_analysis_for_text).
+   Learn more about [AutoML Text](https://cloud.google.com/vertex-ai/docs/text-data/sentiment-analysis/train-model).
 
 
 [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)
@@ -235,7 +218,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Action recognition for video data](https://cloud.google.com/vertex-ai/docs/training-overview#action_recognition_for_videos).
+   Learn more about [AutoML Video](https://cloud.google.com/vertex-ai/docs/video-data/action-recognition/train-model).
 
 
 [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)
@@ -252,7 +235,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Classification for video data](https://cloud.google.com/vertex-ai/docs/training-overview#classification_for_videos).
+   Learn more about [AutoML Video](https://cloud.google.com/vertex-ai/docs/video-data/classification/train-model).
 
 
 [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)
@@ -269,5 +252,5 @@ The steps performed include:
 
 ```
 
-   Learn more about [Object tracking for video data](https://cloud.google.com/vertex-ai/docs/training-overview#object_tracking_for_videos).
+   Learn more about [AutoML Video](https://cloud.google.com/vertex-ai/docs/video-data/object-tracking/train-model).
 

notebooks/official/bigquery_ml/README.md

@@ -15,25 +15,5 @@ The steps performed include:
 
 ```
 
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
-
-
-[Get started with BigQuery ML Training](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/bigquery_ml/get_started_with_bqml_training.ipynb)
-
-```
-Learn how to use `BigQueryML` for training with `Vertex AI`.
-
-The steps performed include:
-
-- Create a local BigQuery table in your project
-- Train a BigQuery ML model
-- Evaluate the BigQuery ML model
-- Export the BigQuery ML model as a cloud model
-- Upload the exported model as a `Vertex AI Model` resource
-- Hyperparameter tune a BigQuery ML model with `Vertex AI Vizier`
-- Automatically register a BigQuery ML model to `Vertex AI Model Registry`
-
-```
-
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
+   Learn more about [BigQuery ML](https://cloud.google.com/bigquery-ml/docs/introduction).
 

notebooks/official/bigquery_ml/get_started_with_bqml_training.ipynb

@@ -61,6 +61,7 @@
       "source": [
         "## Overview\n",
         "\n",
+        "\n",
         "This tutorial demonstrates how to use Vertex AI in production. This tutorial covers get started with BigQuery ML training.\n",
         "\n",
         "Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml)."
@@ -154,8 +155,7 @@
         "! pip3 install --upgrade pyarrow \\\n",
         "                        google-cloud-aiplatform \\\n",
         "                        google-cloud-bigquery \\\n",
-        "                        google-cloud-bigquery-storage \\\n",
-        "                        db-dtypes $USER_FLAG -q"
+        "                        google-cloud-bigquery-storage $USER_FLAG -q"
       ]
     },
     {

notebooks/official/experiments/README.md

@@ -55,36 +55,3 @@ The steps performed include:
 
    Learn more about [Vertex AI Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction).
 
-
-[Get started with Vertex AI Experiments](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/experiments/get_started_with_vertex_experiments.ipynb)
-
-```
-Learn how to use `Vertex AI Experiments` when training with `Vertex AI`.
-
-The steps performed include:
-
-- Local (notebook) Training
-    - Create an experiment
-    - Create a first run in the experiment
-    - Log parameters and metrics
-    - Create artifact lineage
-    - Visualize the experiment results
-    - Execute a second run
-    - Compare the two runs in the experiment
-- Cloud (`Vertex AI`) Training
-    - Within the training script:
-        - Create an experiment
-        - Log parameters and metrics
-        - Create artifact lineage
-    - Create a `Vertex AI Training` custom job
-    - Execute the custom job
-    - Visualize the experiment results
-
-```
-
-   Learn more about [Vertex AI Experiments](https://cloud.google.com/vertex-ai/docs/experiments/intro-vertex-ai-experiments).
-
-   Learn more about [Vertex ML Metadata](https://cloud.google.com/vertex-ai/docs/ml-metadata).
-
-   Learn more about [Vertex AI Training](https://cloud.google.com/vertex-ai/docs/training/custom-training).
-

notebooks/official/model_monitoring/README.md

@@ -15,128 +15,6 @@ The steps performed include:
    Learn more about [Vertex AI Model Monitoring for batch predictions](https://cloud.google.com/vertex-ai/docs/model-monitoring/model-monitoring-batch-predictions).
 
 
-[Vertex AI Model Monitoring for AutoML tabular models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_automl.ipynb)
-
-```
-Learn to use the `Vertex AI Model Monitoring` service to detect feature skew and drift in the input predict requests, for AutoML tabular models.
-
-The steps performed include:
-
-- Train an `AutoML` model.
-- Deploy the `Model` resource to the `Endpoint` resource.
-- Configure the `Endpoint` resource for model monitoring.
-- Generate synthetic prediction requests for skew.
-- Wait for email alert notification.
-- Generate synthetic prediction requests for drift.
-- Wait for email alert notification.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
-[Vertex AI Model Monitoring for batch prediction in AutoML image models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_automl_image_batch.ipynb)
-
-```
-Learn how to use `Vertex AI Model Monitoring` with `Vertex AI Batch Prediction` with an AutoML image classification model to detect an out of distribution image.
-
-The steps performed include:
-
-1. Train an AutoML image classification model.
-2. Submit a batch prediction containing both in and out of distribution images.
-3. Use Model Monitoring to calculate anomaly score on each image.
-4. Identify the images in the batch prediction request that are out of distribution.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
-[Vertex AI Model Monitoring for custom tabular models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_custom.ipynb)
-
-```
-Learn to use the `Vertex AI Model Monitoring` service to detect feature skew and drift in the input predict requests, for custom tabular models.
-
-The steps performed include:
-
-- Download a pre-trained custom tabular model.
-- Upload the pre-trained model as a `Model` resource.
-- Deploy the `Model` resource to the `Endpoint` resource.
-- Configure the `Endpoint` resource for model monitoring.
-- Generate synthetic prediction requests for skew.
-- Wait for email alert notification.
-- Generate synthetic prediction requests for drift.
-- Wait for email alert notification.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
-[Vertex AI Model Monitoring for custom tabular models with TensorFlow Serving container](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_custom_tf_serving.ipynb)
-
-```
-Learn to use the `Vertex AI Model Monitoring` service to detect feature skew and drift in the input predict requests, for custom tabular models, using a custom deployment container.
-
-The steps performed include:
-
-- Download a pre-trained custom tabular model.
-- Upload the pre-trained model as a `Model` resource.
-- Deploying the `Model` resource to an `Endpoint` resource with `TensorFlow Serving` serving binary.
-- Configure the `Endpoint` resource for model monitoring.
-- Generate synthetic prediction requests for skew.
-- Wait for email alert notification.
-- Generate synthetic prediction requests for drift.
-- Wait for email alert notification.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
-[Vertex AI Model Monitoring for setup for tabular models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_setup.ipynb)
-
-```
-Learn to setup the `Vertex AI Model Monitoring` service to detect feature skew and drift in the input predict requests.
-
-The steps performed include:
-
-- Download a pre-trained custom tabular model.
-- Upload the pre-trained model as a `Model` resource.
-- Deploy the `Model` resource to the `Endpoint` resource.
-- Configure the `Endpoint` resource for model monitoring.
-    - Skew and drift detection for feature inputs.
-    - Skew and drift detection for feature attributions.
-- Automatic generation of the `input schema` by sending 1000 prediction request.
-- List, pause, resume and delete monitoring jobs.
-- Restart monitoring job with predefined `input schema`.
-- View logged monitored data.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
-[Vertex AI Model Monitoring for XGBoost models](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/get_started_with_model_monitoring_xgboost.ipynb)
-
-```
-Learn to use the `Vertex AI Model Monitoring` service to detect feature skew and drift in the input predict requests for XGBoost models.
-
-The steps performed include:
-
-- Download a pre-trained XGBoost model.
-- Upload the pre-trained model as a `Model` resource.
-- Deploy the `Model` resource to the `Endpoint` resource.
-- Configure the `Endpoint` resource for model monitoring:
-  - drift detection only -- no access to training data.
-  - predefine the input schema to map feature alias names to the unnamed array input to the model.
-- Generate synthetic prediction requests for drift.
-
-```
-
-   Learn more about [Vertex AI Model Monitoring](https://cloud.google.com/vertex-ai/docs/model-monitoring).
-
-
 [Vertex AI Model Monitoring with Explainable AI Feature Attributions](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_monitoring/model_monitoring.ipynb)
 
 ```

notebooks/official/model_registry/README.md

@@ -17,5 +17,5 @@ The steps performed include:
 
    Learn more about [Vertex AI Model Registry](https://cloud.google.com/vertex-ai/docs/model-registry/introduction).
 
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
+   Learn more about [BigQuery ML](https://cloud.google.com/bigquery-ml/docs/introduction).
 

notebooks/official/pipelines/README.md

@@ -285,24 +285,3 @@ The steps performed include:
 
    Learn more about [Vertex AI Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction).
 
-
-[BQML and AutoML - Experimenting with Vertex AI](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/rapid_prototyping_bqml_automl.ipynb)
-
-```
-Learn how to use `Vertex AI Predictions` for rapid prototyping a model.
-
-The steps performed include:
-
-- Creating a BigQuery and Vertex AI training dataset.
-- Training a BigQuery ML and AutoML model.
-- Extracting evaluation metrics from the BigQueryML and AutoML models.
-- Selecting the best trained model.
-- Deploying the best trained model.
-- Testing the deployed model infrastructure.
-
-```
-
-   Learn more about [AutoML components](https://cloud.google.com/vertex-ai/docs/pipelines/vertex-automl-component).
-
-   Learn more about [BigQuery ML components](https://cloud.google.com/vertex-ai/docs/pipelines/bigqueryml-component).
-

notebooks/official/tabnet/README.md

@@ -12,7 +12,9 @@ The steps performed are:
 
 ```
 
-   Learn more about [Tabular Workflow for TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+   Learn more about [Vertex AI TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+
+   Learn more about [Vertex Explainable AI](https://cloud.google.com/vertex-ai/docs/explainable-ai/overview).
 
 
 [Vertex AI TabNet](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tabnet/tabnet_vertex_tutorial.ipynb)
@@ -30,5 +32,7 @@ The steps performed are:
 
 ```
 
-   Learn more about [Tabular Workflow for TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+   Learn more about [Vertex AI TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+
+   Learn more about [Vertex AI Hyperparameter Tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview).
 

notebooks/official/tabular_workflows/README.md

@@ -11,7 +11,9 @@ The steps performed include:
 
 ```
 
-   Learn more about [Tabular Workflow for TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+   Learn more about [Vertex AI TabNet](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/tabnet).
+
+   Learn more about [Vertex AI Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction).
 
 
 [Wide & Deep Pipeline](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tabular_workflows/wide_and_deep_on_vertex_pipelines.ipynb)
@@ -26,5 +28,7 @@ The steps performed include:
 
 ```
 
-   Learn more about [Tabular Workflow for Wide & Deep](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/wide-and-deep).
+   Learn more about [Vertex AI Wide & Deep](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/wide-and-deep).
+
+   Learn more about [Vertex AI Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction).
 

notebooks/official/training/README.md

@@ -1,22 +1,4 @@
 
-[Get started with Vertex AI Distributed Training](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/training/get_started_with_vertex_distributed_training.ipynb)
-
-```
-Learn how to use `Vertex AI Distributed Training` for when training with `Vertex AI`.
-
-The steps performed include:
-
-- `MirroredStrategy`: Train on a single VM with multiple GPUs.
-- `MultiWorkerMirroredStrategy`: Train on multiple VMs with automatic setup of replicas.
-- `MultiWorkerMirroredStrategy`: Train on multiple VMs with fine grain control of replicas.
-- `ReductionServer`: Train on multiple VMS and sync updates across VMS with `Vertex AI Reduction Server`.
-- `TPUTraining`: Train with multiple Cloud TPUs.
-
-```
-
-   Learn more about [Vertex AI Distributed Training](https://cloud.google.com/vertex-ai/docs/training/distributed-training).
-
-
 [Run hyperparameter tuning for a TensorFlow model](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/training/hyperparameter_tuning_tensorflow.ipynb)
 
 ```

notebooks/official/training/get_started_with_vertex_distributed_training.ipynb

@@ -61,7 +61,8 @@
       "source": [
         "## Overview\n",
         "\n",
-        "This tutorial demonstrates how to use the Vertex AI Python client library to do distrbuted training of a TensorFlow model.\n",
+        "\n",
+        "This tutorial demonstrates how to use Vertex in production. This tutorial covers get started with Vertex Distributed Training. \n",
         "\n",
         "*Note:* There are incompatibilities between Colab and Docker and the Docker section may not work until resolved by the platform.\n",
         "\n",
@@ -76,7 +77,7 @@
       "source": [
         "### Objective\n",
         "\n",
-        "In this tutorial, you learn how to use `Vertex AI Distributed Training` when training with `Vertex AI`.\n",
+        "In this tutorial, you learn how to use `Vertex AI Distributed Training` for when training with `Vertex AI`.\n",
         "\n",
         "This tutorial uses the following Google Cloud ML services:\n",
         "\n",

notebooks/official/workbench/README.md

@@ -83,7 +83,7 @@ The steps performed include:
 
    Learn more about [Vertex AI Workbench](https://cloud.google.com/vertex-ai/docs/workbench/introduction).
 
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
+   Learn more about [BigQuery](https://cloud.google.com/bigquery).
 
 
 [Build a fraud detection model on Vertex AI](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/workbench/fraud_detection/fraud-detection-model.ipynb)
@@ -127,7 +127,7 @@ The steps performed include:
 
    Learn more about [Vertex AI Workbench](https://cloud.google.com/vertex-ai/docs/workbench/introduction).
 
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
+   Learn more about [BigQuery ML](https://cloud.google.com/bigquery-ml/docs/managing-models-vertex).
 
 
 [Inventory prediction on ecommerce data using Vertex AI](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/workbench/inventory-prediction/inventory_prediction.ipynb)
@@ -194,7 +194,7 @@ The steps performed include:
 
    Learn more about [Vertex AI Workbench](https://cloud.google.com/vertex-ai/docs/workbench/introduction).
 
-   Learn more about [BigQuery ML](https://cloud.google.com/vertex-ai/docs/beginner/bqml).
+   Learn more about [BigQuery ML](https://cloud.google.com/bigquery-ml/docs/managing-models-vertex).
 
 
 [Sentiment Analysis using AutoML Natural Language and Vertex AI](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/workbench/sentiment_analysis/Sentiment_Analysis.ipynb)