

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.
Top Positive Mentions
Spinning up models without writing code
100% positive (41 mentions)
Getting from idea to working model in hours
100% positive (26 mentions)
Tracking experiments without losing your mind
100% positive (23 mentions)
Top Negative Mentions
AI pricing model
67% negative (3 mentions)
Today, we are excited to take the next step in our mission to provide unparalleled flexibility and performance by officially introducing support for Google Vertex AI and Intel® Gaudi® AI accelerators.
: With help from Google and Intel, Big Blue brings new automation to Db2
Data science platform Tredence has detailed its suite of agentic AI accelerators, developed in close collaboration with Google Cloud. But wait, agentic Tredence deployed Gemini Enterprise, Vertex AI (Google’s platform for building, deploying and scaling machine learning and generative models) and BigQuery (Google Cloud’s managed, serverless data warehouse for high-speed analysis of petabyte-scale datasets using standard SQL queries and built-in machine learning capabilities) as the foundation of a complete data and AI platform modernisation.
Visit Vertex AI's official website for product details and getting started.
Comprehensive guides and API references for using Vertex AI effectively.
Detailed information on the pricing structure for Vertex AI services.