Installation, management and maintenance of MLOps infrastructure and system
We provide installation, management and maintenance of all processes that bring your machine learning models to life with open source modern tools.
- Providing a model development environment
- Troubleshooting problems in using model development tools and libraries
- Turning models into docker containers
- Recording of model development studies
- Selection of the best model
- API development for model presentation
- Recording the forecast results in the database
- Drifting and deteriorating models: Concept and Data Drift detection
- Serving models from a server in the datacenter, the cloud, or Kubernetes
- ML Pipelines
- Recording of model development studies
- Creating custom python packages
- Use of IaC (Infrastructure as Code) tools such as Terraform to prepare infrastructure
- Turning the model into a system service and monitoring it with Monitoring tools
- Creating a CI/CD Pipeline for MLOps
- Model deployment automation
Machine learning, artificial intelligence…
Everyone is doing it, at least talking about it, so let’s not fall behind
What are we going to do?
Let’s hire a few data scientists immediately so we don’t miss the train.
It might be a good start, but not enough.
You should also establish an environment, infrastructure, system, and culture, where the data scientists will be productive and reap the benefits of their work.
Come to MLOps. These are the goods of the open source ship.
If you don’t want the team’s efforts to be in vain, the models to be wasted and your dreams to be ruined, we can help you.
