MLOps Zoomcamp Course

This is repository for MLOps Zoomcamp course from DataTalks.Club

Objective

The goal of this course is to understand the usage of different MLOps processes in the Machine Learning pipeline built. Understanding of different services that help in building the production ready ML codes is explored.

Folders

Each folder has the homework for the respective week and the project folder has details of the final project executed at the end of course using the topics learnt over all weeks

Tools and Technologies Used

• Experiment Tracking and Model Registry : MLflow
• Workflow Orchestration : Prefect
• Containerization : Docker and Docker Compose
• Model Deployment : Deployment as web service using Flask, Docker and MLflow
• Model Monitoring : Evidently AI, Grafana and Prometheus
• Best Practices : Unit tests, Integration test, Linting, Code Formatting, Makefile and Pre-commit hooks