Everything you need for AI Performance in one platform.
We decided that Docs should have prime location.
Fundamentals of ML observability
Metrics, feature importance and more
We’re excited ???? to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
Your data science team is growing, meaning more models are heading to production. This calls for a standard way to build, train, serve, deploy, and monitor your models. While this may be a given – how you build this ML infrastructure is still a long and winding road, and how you monitor your platform is still up in the air.
Different approaches call for different methods, and this ebook will conveniently break down how to build an ML platform, using popular open-source tools. You’ll also gain valuable insights into leveraging Aporia’s customizable ML monitoring to ensure your model is driving its intended value.
Building an ML platform using open-source tools – DVC, Cookiecutter, MLFlow, FastAPI
Teach you the basic principles of how to build your own ML platform
Cloud Native DevOps Infrastructure for ML Platforms - Kubernetes, Helm, Pulumi, Poetry
Monitoring your ML models with Aporia, an important step to putting Responsible AI into practice.
