MLOps process for ML Model Deployment
Customer
Swiss Pharmaceutical Company
Established a common development framework, as well as a standardised release process enabling faster and more efficient ML model deployment
Challenge
- Data Science team at client has been working on several ML projects that need to be put into production
- Goal of this project was to provide an initial MLOps process to deploy models into production
Solution
- Consulting and implementation of right technology stack combined with establishing a proper process
- Established common framework (Kedro) to develop ML models. Setup a standard release process to deploy ML use cases
- Defined tech stack needed for future use cases
Business impact
- Established common development framework to standardise processes
- Best practices put in place for development and release of software/ML models
- Built initial infrastructure enabling reproducible ML pipeline creation on-premise