Using scikit-learn for Data Mining: Feature Engineering, Parallel Processing, Pipelines, and Model Persistence
This article demonstrates how to perform data mining with scikit-learn by detailing the full workflow—from data acquisition and feature engineering, through parallel and pipeline processing, to automated hyper‑parameter tuning and model persistence—using the Iris dataset as an example.
