2023-today
Machine Learning Operations platform for driver behavior adaptivity
Goal: Develop a cloud platform based on the Azure platform. The platform presents an efficient space for automatic training, validation, testing, and monitoring of an ML model that is able to learn user preferences. The platform provides, Data Engineering, Model development, Continuous Development/ Integration, model monitoring
- Task: MLOPS platform
- Role: Project Lead
- Tools management: Jira, git, Bitbucket, Confluence, MLOPS, docker
- Libraries: Scikitlean
- IDE: Visual Studio Code
- Implemented stages: Data acquisition, data process, data versioning (DVC), Automatic training pipeline, ML deployment as service on Azure