Saving Machine Learning Models by joblib

h1ros

Goal¶

This post aims to introduce how to save the machine learning model using joblib.

In [4]:

import pandas as pd
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.datasets import load_boston
import joblib

In [5]:

boston = load_boston()
X, y = boston.data, boston.target

In [6]:

reg = LinearRegression()
reg.fit(X, y)

Out[6]:

LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,
         normalize=False)

In [7]:

joblib.dump(reg, 'linear_regression.pkl')

Out[7]:

['linear_regression.pkl']

In [11]:

!ls | grep linear*pkl

linear_regression.pkl

In [13]:

loaded_reg = joblib.load('linear_regression.pkl')
loaded_reg

Out[13]:

LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,
         normalize=False)