Google has announced that generative AI support on the Vertex AI, Google Cloud’s machine learning platform as a service (ML PaaS) product, is now generally available.
Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset. Vertex AI provides several options for model training: AutoML lets you train tabular, image, text, or video data without writing code or preparing data splits.
Vertex AI is a machine learning (ML) platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.
Vertex AI provides several options for model training:
AutoML lets you train tabular, image, text, or video data without writing code or preparing data splits.
Custom training gives you complete control over the training process, including using your preferred ML framework, writing your own training code, and choosing hyperparameter tuning options.
After you deploy your models, use Vertex AI’s end-to-end MLOps tools to automate and scale projects throughout the ML lifecycle. These MLOps tools are run on fully-managed infrastructure that you can customize based on your performance and budget needs.
You can use the Vertex AI SDK for Python to run the entire machine learning workflow in Vertex AI Workbench, a Jupyter notebook-based development environment. Other available interfaces include the Google Cloud Console, the gcloud command line tool, client libraries, and Terraform (limited support).
