model_creation.py

import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split,cross_val_score
#from sklearn.externals import joblib
import joblib
from sklearn.metrics import mean_squared_error
import matplotlib.pyplot as plt
from math import sqrt
import os

df = pd.read_csv('./data.csv')

i = list(df.columns.values)
i.pop(i.index('SalePrice'))
df0 = df[i+['SalePrice']]
df = df0.select_dtypes(include=['integer','float'])
X = df[list(df.columns)[:-1]]
y = df['SalePrice']
X_train, X_test, y_train, y_test = train_test_split(X, y)

regressor = LinearRegression()
regressor.fit(X_train, y_train)
joblib.dump(regressor, './model.pkl')