The template takes you one step toward reproducibility with your personalized instance.
An open-source package that manages the complete ML lifecycle including experimentation, reproducibility, deployment, and central model registry.
Use MLFlow to better track ML experiments.
Quick start on GCP with a ready-to-use code and project
Track models with Managed Experiment Tracking and Model Registry service
Deploy model within Platform infrastructure for seamless and trouble free operation
IAM: manage roles and permissions on user and domain level, or access with service account
Manage multiple environments (dev, testing, staging, etc.), trace activity and changes
The Managed Experiment Tracking with MLFlow blueprint includes industry best practices in the form of ready-to-use codes or templates delivered to you, on your infrastructure, through seamless deployment for sustainable quality.
The platform allows you to standardize workflows. Developing the models with maximum efficiency will not interfere with integration and will manage the risk of a lower ROI due to productizing and integration.
Applying best practices in production requires continual improvement and support. Leveraging on the blueprint repository of Aliz Intelligence Platform ensures that the technology is always up to date.
This out-of-the-box set-up is enterprise ready and powered by Terraform.