Migrate your applications to Vertex AI

Vertex AI brings together AI Platform and legacy AutoML services under one unified UI and API to simplify the process of building, training, and deploying machine learning models. With Vertex AI, you can move from experimentation to production faster, efficiently discover patterns and anomalies, make better predictions and decisions, and stay agile in the face of changing priorities and market conditions. This page helps determine the changes you need to make when you migrate your applications from legacy AutoML or AI Platform to Vertex AI.

Vertex AI supports all features and models available in legacy AutoML and AI Platform. However, the client libraries do not support client integration backward compatibility. In other words, you must plan to migrate your resources to benefit from Vertex AI features.

This page compares the API methods used to complete common user journeys so that you can see how your project's applications could be updated to use the Vertex AI API.

Common user journeys

Select the tab for your product, and then click a user journey to see how the Vertex AI API methods compare with the API methods used by your existing applications.

Legacy AutoML Natural Language

Click one of the following user journeys:

Legacy AutoML Natural Language: Train and deploy a text classification model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Natural Language and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Natural Language Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.locations.models.deploy projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.models.predict projects.locations.endpoints.predict

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Legacy AutoML Natural Language: Train and deploy a text entity extraction model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Natural Language and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Natural Language Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.locations.models.deploy projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.models.predict projects.locations.endpoints.predict

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Legacy AutoML Natural Language: Train and deploy a text sentiment model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Natural Language and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Natural Language Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.locations.models.deploy projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.models.predict projects.locations.endpoints.predict

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Legacy AutoML Video Intelligence

Click one of the following user journeys:

Legacy AutoML Video Intelligence: Train and deploy an object tracking model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Video and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Video Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get

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Legacy AutoML Video Intelligence: Train and deploy a video classification model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Video and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Video Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get

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Legacy AutoML Vision

Click one of the following user journeys:

Legacy AutoML Vision: Train and deploy an image classification model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Vision and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Vision Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.locations.models.deploy projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.models.predict projects.locations.endpoints.predict
Train and export an Edge model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
projects.locations.models.export projects.locations.models.export

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Legacy AutoML Vision: Train and deploy an object detection model

Read about the differences between the legacy AutoML API and the Vertex AI API, read about differences between the legacy AutoML Vision and Vertex AI products, and then use the following table to help migrate your API.

Step Legacy AutoML Vision Vertex AI
Create a dataset projects.locations.datasets.create projects.locations.datasets.create
projects.locations.datasets.importData projects.locations.datasets.import
Train a model projects.locations.models.create projects.locations.trainingPipelines.create
projects.locations.trainingPipelines.get
Evaluate the model projects.locations.models.modelEvaluations.list projects.locations.models.evaluations.list
projects.locations.models.modelEvaluations.get projects.locations.models.evaluations.get
Make batch predictions projects.locations.models.batchPredict projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.locations.models.deploy projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.models.predict projects.locations.endpoints.predict

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AI Platform

Click one of the following user journeys:

AI Platform: Train and deploy an XGBoost model with hosted runtime versions

Read about the differences between the AI Platform and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Vertex AI
Train a model projects.jobs.create projects.locations.customJobs.create
projects.jobs.get projects.locations.customJobs.get
Deploy the model projects.models.create projects.locations.models.upload
projects.models.versions.create
Make batch predictions AI Platform batch prediction is not supported for XGBoost. projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.predict projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.endpoints.predict

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AI Platform: Train and deploy a scikit-learn model with hosted runtime versions

Read about the differences between the AI Platform and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Vertex AI
Train a model projects.jobs.create projects.locations.customJobs.create
projects.jobs.get projects.locations.customJobs.get
Deploy the model projects.models.create projects.locations.models.upload
projects.models.versions.create
Make batch predictions AI Platform batch prediction is not supported for scikit-learn. projects.locations.batchPredictionJobs.create
projects.locations.batchPredictionJobs.get
Make online predictions projects.predict projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.endpoints.predict

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AI Platform: Train and deploy a TensorFlow model with custom containers

Read about the differences between the AI Platform and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Vertex AI
Train a model projects.jobs.create projects.locations.customJobs.create
projects.jobs.get projects.locations.customJobs.get
Deploy the model projects.models.create projects.locations.models.upload
projects.models.versions.create
Make batch predictions projects.jobs.create projects.locations.batchPredictionJobs.create
projects.jobs.get projects.locations.batchPredictionJobs.get
Make online predictions projects.predict projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.endpoints.predict

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AI Platform: Train and deploy a TensorFlow model with hosted runtime versions

Read about the differences between the AI Platform and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Vertex AI
Train a model projects.jobs.create projects.locations.customJobs.create
projects.jobs.get projects.locations.customJobs.get
Deploy the model projects.models.create projects.locations.models.upload
projects.models.versions.create
Make batch predictions projects.jobs.create projects.locations.batchPredictionJobs.create
projects.jobs.get projects.locations.batchPredictionJobs.get
Make online predictions projects.predict projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.endpoints.predict

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AI Platform Prediction: Submit a batch prediction job for a hosted TensorFlow model

Read about the differences between the AI Platform Prediction and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Prediction Vertex AI
Train a model projects.jobs.create projects.locations.customJobs.create
projects.jobs.get projects.locations.customJobs.get
Deploy the model projects.models.create projects.locations.models.upload
projects.models.versions.create
Make batch predictions projects.jobs.create projects.locations.batchPredictionJobs.create
projects.jobs.get projects.locations.batchPredictionJobs.get
Make online predictions projects.predict projects.locations.endpoints.create
projects.locations.endpoints.deployModel
projects.locations.endpoints.predict

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AI Platform Training: Submit a hyperparameter tuning training job with TensorFlow

Read about the differences between the AI Platform Training and Vertex AI products, and then use the following table to help migrate your API.

Step AI Platform Training Vertex AI
Train a model projects.jobs.create projects.locations.hyperparameterTuningJobs.create
projects.jobs.get projects.locations.hyperparameterTuningJobs.get

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What's next