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@kururu-abdo
Created July 19, 2023 18:41
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from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
Input=[('scale',StandardScaler()),('model',LinearRegression())]
pipe=Pipeline(Input)
pipe.fit(df[['horsepower' ,'col1']],y)
ypipe=pipe.predict(df[['horsepower' ,'col1'])
ypipe[0:10]
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