Welcome to the MlOps Zoomcamp 2024 repository! Here, you can find the completed homework assignments for each module.
| Module | Topics | Homework |
|---|---|---|
| Module 1: Introduction 🚀 | - What is MLOps - MLOps maturity model - Running example: NY Taxi trips dataset - Why do we need MLOps - Course overview - Environment preparation |
Homework |
| 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 - MLflow in practice |
Homework |
| Module 3: Orchestration and ML Pipelines 🚀 | - Workflow orchestration - Mage |
Homework |
| 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 |
Homework |
For this course, you'll need to have the following software installed on your computer:
- Docker and Docker-Compose
- Python 3 (e.g. via Anaconda)
- MLflow
- Mage Ai
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent