- Evaluate the type of machine learning blocks generated.
- Evaluate the required scalability for operationalization
- Evaluate the required level of automation
- Evaluate the internal expertise when it comes to ML Operation
- Evaluate the working environment of data scientists and data engineers
- The high-level design of MLOps environment and validation
- Test cases design
- echnical review and validation of the design and architecture
- The low-level design of MLOps environment
- Implementation of the environment (staging/production)
- Testing cases
- Training of the identified resources on how to manage and use the environment
- Final report with a roadmap
Deliverables
The following deliverables to be expected during and after our mandate:
The implementation of a variable environment in MLOp’s
MLOp’s training session
High level and low level design document
A report with recommendations and roadmap