What's included

• MLOps Workflow

  - Scalable Model Infrastructure: Implementation of a scalable infrastructure for deploying machine learning models, including containerization and orchestration. - Automated Model Training Pipeline: Development of an automated pipeline for model training, validation, and deployment, ensuring reproducibility and efficiency. - Monitoring and Logging System: Integration of a comprehensive monitoring and logging system to track model performance, data drift, and system health. - Continuous Integration/Continuous Deployment (CI/CD): Establishment of CI/CD pipelines for seamless integration of model updates and automated deployment to production. - Documentation and Knowledge Transfer: Provision of detailed documentation and knowledge transfer sessions to enable the client's team to maintain and extend the MLOps workflow.