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| # Persist pipeline to disk | |
| pipeline.fit(x_train, y_train) | |
| joblib.dump(pipeline, 'model.joblib') | |
| # Load pipeline and make prediction | |
| pipeline = joblib.load('model.joblib') | |
| y_hat = pipeline.predict(x) |
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