These are my notes of the Udacity Nanodegree Machine Learning DevOps Engineer.
The nanodegree is composed of four modules:
- Clean Code Principles
- Building a Reproducible Model Workflow
- Deploying a Scalable ML Pipeline in Production
- ML Model Scoring and Monitoring
Each module has a folder with its respective notes; you need to go to each module folder and follow the Markdown file in it.
Udacity requires the submission of a project for each module; these are the repositories of the projects I submitted:
- Predicting Customer Churn with Production-Level Software: customer_churn_production.
- A Reproducible Machine Learning Pipeline for Short-Term Rental Price Prediction in New York City: ml_pipeline_rental_prices.
- Deploying a Machine Learning Model on Heroku with FastAPI: census_model_deployment_fastapi.
- A Dynamic Risk Assessment System — Monitoring of a Customer Churn Model: churn_model_monitoring.
Mikel Sagardia, 2022.
No guarantees.