One AI platform, every ML tool you need

With so much data at our fingertips, many organisations are utilising machine learning to generate insightful predictions and improve their apps. But most teams have varying levels of machine learning expertise, ranging from novice all the way to experts.

To accelerate AI innovation, you need a platform that can help you build expertise for those novice users, and provide a flexible environment for those experts.

Introducing Vertex AI from Google Cloud

Vertex AI unifies Google Cloud’s existing ML offerings into a single environment for efficiently building and managing the lifecycle of ML projects. It provides tools for every step of the machine learning workflow across different model types, for varying levels of machine learning expertise.
In Vertex AI, you can now easily train and compare models using AutoML or custom code training and all your models are stored in one central model repository.  These models can now be deployed to the same endpoints on Vertex AI.

Train models without code, minimal expertise required

Take advantage of AutoML to build models in less time. Use Vertex AI with state-of-the-art, pre-trained APIs for computer vision, language, structured data, and conversation.

Build advanced ML models with custom tooling

Vertex AI’s custom model tooling supports advanced ML coding, with nearly 80% fewer lines of code required to train a model with custom libraries than competitive platforms (watch Codelab).

Manage your models with confidence

Vertex AI’s MLOps tools remove the complexity of model maintenance, such as Vertex AI Pipelines, to streamline running ML pipelines, and Vertex AI Feature Store to serve, and use AI technologies as ML features.

Explore key resources

AI Simplified video series

Learn how to use Vertex AI to manage datasets, build and train models using AutoML, or build custom models from scratch, and build Vertex Pipelines

Watch sessions from Google’s Applied ML Summit

Register now

Vertex AI Best Practice Guide

Vertex AI Best Practice Guide

Explore conversational AI

Convert text into natural-sounding speech with AI-powered Text-to-Speech or build conversational AI with Dialogflow.

Google named a Leader in The Forrester Wave: AI Infrastructure, Q4 2021

Download the report

Harness the power of machine learning with Google Cloud

Machine Learning

Digicloud’s article, Start using Machine Learning with Google, it’s easier than you think, explains the ML journey and how organisations at any stage of the ML journey can benefit from the power of Google Cloud tools.

For some organisations and in some circumstances, ML may not be the right solution, and this is where guidance is needed from the likes of Digicloud’s partner network. We also come across customers that would like to embark on an ML journey but are not sure how to get started. Key to ML is having enough and accurate data. Our partners can help architect, build and operate data pipelines to help customers operationalise ML in production.