Vertex AI is a machine learning (ML) platform developed by Google Cloud. It provides a unified environment for training, deploying, and managing ML models and AI applications, as well as customizing large language models (LLMs) for use in AI-powered applications. Vertex AI offers a range of tools and services for data scientists and ML engineers to efficiently and responsibly automate, standardize, and manage ML projects throughout the entire development life cycle.
Some key features and capabilities of Vertex AI include:
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Data and AI integration: Vertex AI is integrated with Google Cloud services such as Dataproc, Dataflow, and BigQuery, allowing seamless integration of data and ML workflows.
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AutoML: Users can build state-of-the-art ML models without code by using AutoML to determine the optimal model architecture for image, tabular, text, or video prediction tasks. Custom models can also be built using Notebooks.
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Training and deployment: Vertex AI Training offers fully managed training services, while Vertex AI Vizier provides optimized hyperparameters for maximum predictive accuracy. Users can register trained models in the Vertex AI Model Registry for versioning and hand-off to production, which integrates with validation and deployment features such as model evaluation and endpoints.
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Monitoring and governance: Vertex AI provides model monitoring capabilities to track performance and ensure models are functioning as expected in production. Users can also govern their ML projects by managing access controls, monitoring resource usage, and maintaining compliance with data privacy regulations.
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Collaboration and scalability: Vertex AI enables teams to collaborate using a common toolset and scale applications using the benefits of Google Cloud. The platform is designed to reduce the work needed to maintain model performance in production, allowing data scientists and ML engineers to focus on innovation and code.
