Master Linear Regression in Python: Step-by-Step Tutorial 📊
Learn how to perform linear regression prediction with Python using pandas, scikit-learn, and more. Perfect for data science enthusiasts and coders looking to enhance their skills!
AC
27.6K views • Apr 10, 2023
About this video
#Coded by Andrew C
import pandas as pd
import numpy as np
from sklearn import datasets
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
wine_dataset = datasets.load_wine()
wine = pd.DataFrame(wine_dataset.data, columns=wine_dataset.feature_names)
X = wine[['ash']]
Y = wine['alcohol']
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.3, random_state=1)
model = LinearRegression()
model.fit(X_train, Y_train)
new_RM = np.array([2.5]).reshape(-1,1)
print("Prediction: " + str(model.predict(new_RM)))
import pandas as pd
import numpy as np
from sklearn import datasets
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
wine_dataset = datasets.load_wine()
wine = pd.DataFrame(wine_dataset.data, columns=wine_dataset.feature_names)
X = wine[['ash']]
Y = wine['alcohol']
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.3, random_state=1)
model = LinearRegression()
model.fit(X_train, Y_train)
new_RM = np.array([2.5]).reshape(-1,1)
print("Prediction: " + str(model.predict(new_RM)))
Video Information
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27.6K
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Duration
0:06
Published
Apr 10, 2023
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