advanced-mlops-databricks

This repo contains notebooks for complete MLOps within Databricks: from model deployment to monitoring.

The source code comes from the course:

Advanced Machine Learning with Databricks

Machine Learning at Scale: Spark, Optuna (hyperparameter optimization) and MLflow.
- Model Development
- Model Optimization
- Model Deployment
Advanced Machine Learning Operations: Workflows (pipelines), Automated testing and Monitoring.
- CI/CD Pipelines
- Unity and Integration Tests
- Model Rollout
- Model Monitoring
- Drift Detection

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
1 Model Development.ipynb		1 Model Development.ipynb
2 Hyperparameter Optimization with Optuna.ipynb		2 Hyperparameter Optimization with Optuna.ipynb
3 Model Deployment.ipynb		3 Model Deployment.ipynb
4 CI-CD Pipeline.ipynb		4 CI-CD Pipeline.ipynb
5 Common Testing.ipynb		5 Common Testing.ipynb
6 Integration Tests.ipynb		6 Integration Tests.ipynb
7 Model Rollout.ipynb		7 Model Rollout.ipynb
8 Model Monitoring.ipynb		8 Model Monitoring.ipynb
9 Drift Monitoring.ipynb		9 Drift Monitoring.ipynb
README.md		README.md

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