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Harnessing the Power of Generative AI with Google Cloud
Generating creative, personalized content like text, images, and video is now easier than ever before, thanks to advances in artificial intelligence...
Custom training in Google Cloud's Vertex AI provides a mechanism for developing machine learning (ML) models with your own defined algorithms while allowing for complex configurations. Using Vertex AI's managed training service, you can operationalize large-scale modeling.
This saves time, effort, and tedious work, allowing developers to focus on other tasks.
Custom training in Vertex AI allows you to train machine learning models using your own algorithms and data, meaning you can use Vertex AI to run training applications based on any ML framework on Google Cloud infrastructure. This gives you full control and flexibility over the model architecture, framework, and training code.
There are many challenges to operationalizing model training, from the time and cost needed to train models to the skills required to manage the compute infrastructure.
Vertex AI helps alleviate these challenges while providing a host of benefits, including:
The custom training workflow on Vertex AI follows this process:
Let's take a look at these steps in more detail.
First, you need to load your data. To follow best practices, it's recommended to use one of these Google Cloud services as your data source:
In addition, you can specify a Vertex AI-managed dataset as a data source to train your mode. By training a custom model and an AutoML model with the same dataset, you can compare performance of the two.
To prepare your data, you need to determine a type of container image to use and package your training application into a supported format based on the chosen container image. Vertex AI runs training applications in a Docker container image, which is a self-contained software package that includes code and dependencies and can run in almost any computing environment. You can either provide the URI of a prebuilt container image or create and upload a custom image.
It's also important to follow the training code best practices for Vertex AI.
A Vertex AI training job performs a range of tasks:
Learn more about the three types of training jobs Vertex AI offers for running your training application. Then, you'll need to choose the compute resources to use for a training job; Vertex AI supports single-node training and distributed training.
Finally, you'll need to select the container configurations you need. These container configurations will change depending on if you're using a pre-built or custom image.
Once your data and application are prepared, you can run your training application by creating one of the following jobs:
You can use the Google Cloud console, Google Cloud CLI, Vertex AI SDK for Python, or the Vertex AI API to create your training job.
Whether you've used AI for custom training and are looking for a better tool or are curious about trying Vertex AI for the first time, there are tons of advantages to leveraging this technology to your benefit.
Vertex AI aims to make your path to digitally transforming with AI technology faster and more effective. As a certified Google partner, we at Promevo can guide you step-by-step on that journey.
Our team has deep expertise in all things Google. We stay on top of product innovations and roadmaps to ensure our clients deploy the latest solutions to drive competitive differentiation with AI.
Through our comprehensive services spanning advisory, implementation, and managed services, you get a true partner invested in realizing your return outcomes — not just delivering tactical tasks. Our solutions help connect workflows across your stack to accelerate insight velocity flowing from Vertex AI models put into production.
Contact us to discover why leading enterprises trust Promevo to maximize their Vertex AI investment.
Vertex AI Training is a managed service within the Google Cloud Vertex AI platform that allows you to train and deploy machine learning (ML) models. It provides a streamlined and scalable environment for handling the entire training process, from data preparation and model building to hyperparameter tuning and deployment.
Vertex AI is an all-in-one ML platform on Google Cloud. You can build, deploy, and manage your models with ease, from data prep to real-time predictions. It allows for a simplified ML workflow, faster results, better models, and less hassle. As a bonus, Vertex AI handles everything, from data to insights, so you can focus on what matters.
Meet the Author
Promevo is a Google Premier Partner that offers comprehensive support and custom solutions across the entire Google ecosystem — including Google Cloud Platform, Google Workspace, ChromeOS, everything in between. We also help users harness Google Workspace's robust capabilities through our proprietary gPanel® software.
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