Google Cloud Unveils Vertex AI, A Machine Learning Platform

Google Cloud Unveils Vertex AI, A Machine Learning Platform

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Google Cloud has launched Vertex AI, a brand new controlled machine learning platform designed to help developers deploy and maintain their Artificial Intelligence (AI) models. 

This new platform enables data scientists and ML engineers to implement Machine Learning Operations (MLOps) and effectively build and manage ML projects throughout the entire development lifecycle. 

According to Google, the platform allows users to deploy AI models faster and takes nearly 80% fewer lines of code to quickly train a model over its competitors.

The Vertex platform is also integrated with  Vizier, known as Google’s AI optimizer, that allows a wide range of developers to automatically tune hyperparameters in machine learning models.  It has come up with an innovative feature called ‘Feature Store’ that is designed to help its users serve, share, and reuse the features of Machine Learning (ML) and revolutionize the deployment process of their models.

Andrew Moore, Vice President and General Manager of Cloud AI and Industry solutions at Google Cloud, remarked that “We had two guiding lights while building Vertex AI: get data scientists and engineers out of the orchestration weeds, and create an industry-wide shift that would make everyone get serious about moving AI out of pilot purgatory and into full-scale production.” 

Benefits Of Vertex AI

  • Get access to Google’s AI toolkit, which includes computer vision, language, interaction, and structured data.
  • Faster Deployment more AI applications with Vertex Vizier that increases the rate of experimentation. The fully controlled Vertex Feature Store, and Vertex Experiments will speed up the deployment of models into production by allowing for faster model selection.
  • MLOps tools including Vertex Continuous Monitoring and Vertex Pipelines streamline the end-to-end ML workflow by eliminating the complexity of self-service model maintenance and repeatability.

This new managed machine learning platform offers three interfaces: a drag-and-drop tool, notebooks for users with a high level of expertise, and BigQuery ML. BigQuery ML, Google’s tool to use SQL queries in an effort to create machine learning models and then execute them in its BigQuery data warehouse.

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Suraj

Suraj Tripathi

Salesforce Consultant | Solution Engineering Head
"Suraj Tripathi, a certified Salesforce Principal Consultant of repute, is a wonderful mentor and leader. A certified Salesforce Architect and a 7X Salesforce Certified Platform Application Developer by passion and profession, Suraj has rich experience in languages such as Aura, HTML, Angular, Bootstrap, APEX, and JavaScript. With more than five years of expertise in Salesforce Development, Suraj has worked on more than 50+ projects out of which 20+ projects were related to Salesforce Integration, Writing Triggers, Batch classes, VisualForce pages, and Aura Components. At Cloud Analogy, he is the backbone of a wide range of projects from all perspectives - technology, architecture, project management, customer stakeholder management, etc. His energy on the floor is difficult to match and his passion to accept nothing but excellence makes him a leader around whom a team can always rally."

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