MLOps Zoomcamp

This repo consists of solutions of MLOps Zoomcamp by DataTalks.Club

Course Link : https://github.com/DataTalksClub/mlops-zoomcamp

Module 1 : Introduction

• What is MLOps
• MLOps maturity model
• Why do we need MLOps

Module 2 : Experiment Tracking and Model Management

• Experiment tracking intro
• Getting started with MLflow
• Experiment tracking with MLflow
• Saving and loading models with MLflow
• Model registry

Module 3 : Orchestration and ML Pipelines

• Workflow orchestration
• Prefect 2.0
• Turning a notebook into a pipeline
• Deployment of Prefect flow

Module 4 : Model Deployment

• Three ways of model deployment : Online (web and streaming) and offline (batch)
• Web service : Model deployment with Flask
• Streaming : Consuming events with AWS Kinesis and Lambda
• Batch : Scoring data offline

Module 5 : Model Monitoring

• Monitoring ML-based services
• Monitoring web services with Prometheus, Evidently, and Grafana
• Monitoring batch jobs with Prefect, MongoDB, and Evidently

Module 6 : Best Practices

• Testing : Unit, Integration
• Python : Linting and Formatting
• Pre-commit hooks and makefiles
• CI/CD (Github Actions)
• Infrastructure as Code (Terraform)

Project

End-to-End project with all the things above