Machine Learning Pipeline.
- Testtesttest
- Testtesttest
- Remove bad records.
- Remove duplicates.
- Scaling data.
- Creating informative features.
- Feature selection.
- Choose model.
- Hyperparameter tuning.
- Model architecture.
- Productionize pipeline.
- Productionize model.
- Store output.
- Evaluate model.
- Monitor model performance over time.