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:
AutoML Natural Language: Train and deploy a text classification model
AutoML Natural Language: Train and deploy a text entity extraction model
AutoML Natural Language: Train and deploy a text sentiment model
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.
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.
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.
Legacy AutoML Video Intelligence
Click one of the following user journeys:
AutoML Video Intelligence: Train and deploy an object tracking model
AutoML Video Intelligence: Train and deploy a video classification model
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.
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.
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.
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.
AI Platform
Click one of the following user journeys:
AI Platform: Train and deploy an XGBoost model with hosted runtime versions
AI Platform: Train and deploy a scikit-learn model with hosted runtime versions
AI Platform: Train and deploy a TensorFlow model with custom containers
AI Platform: Train and deploy a TensorFlow model with hosted runtime versions
AI Platform Prediction: Submit a batch prediction job for a hosted TensorFlow model
AI Platform Training: Submit a hyperparameter tuning training job with TensorFlow
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 |
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 |
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 |
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 |
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 |
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 |
What's next
- Set up a project and a development environment to start using Vertex AI.