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import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
import joblib, os
print("===== STEP 1: Load Data =====")
data = pd.DataFrame({
"Age":[25,45,33,52,23,40,60,48],
"Balance":[1000,5000,2300,8000,1200,4500,9000,3000],
"Exited":[0,1,0,1,0,1,1,0]
})
print("Dataset ready")
print("===== STEP 2: Train Model =====")
X=data[["Age","Balance"]]
y=data["Exited"]
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2)
model=LogisticRegression()
model.fit(X_train,y_train)
os.makedirs("models",exist_ok=True)
joblib.dump(model,"models/pipeline.joblib")
print("Model saved to models/pipeline.joblib")
print("Pipeline finished")
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