Deploy a model in production¶
Once you have trained your model, you can deploy it in production. This section provides several guides in how to deploy your model in different environments.
Overview
Start here to get an overview of the different deployment options.
Deploy in the platform (serverless)
Deploy your model in the platform using the serverless option, using a shared serverless environment.
Deploy in the platform (dedicated)
Deploy your model in the platform using a dedicated deployment and a load balancer.
Deploy in your cloud
Deploy your model in your cloud using the provided Docker image.
Manual serverless deployment
Deploy your model in the platform using the serverless option, but manually configuring the deployment. This is an advanced option.