Vertex AI Pipelines is a service that allows you to orchestrate and automate your machine learning (ML) workflows using pipelines1. A pipeline is a description of an ML workflow, including all of the components in the workflow, how the components are connected as a graph, and the runtime parameters that the pipeline accepts1. Vertex AI Pipelines helps you manage the end-to-end lifecycle of your ML projects, from data preprocessing to model deployment1.
Vertex AI Feature Store is a service that enables you to serve, share, and reuse ML features across different models and projects2. A feature is a measurable property or characteristic of an entity, such as the age of a person or the price of a product2. Vertex AI Feature Store helps you reduce data duplication, ensure data consistency, and improve model performance2.
Vertex AI Experiments is a service that helps you track and compare the performance of different versions of your models3. You can use Vertex AI Experiments to run multiple training jobs with different hyperparameters, architectures, or data sources, and then compare the results using metrics, visualizations, and reports3. Vertex AI Experiments helps you identify the best model for your use case and optimize your model performance3. References:
Vertex AI Pipelines | Google Cloud
Vertex AI Feature Store | Google Cloud
Vertex AI Experiments | Google Cloud
