Program to implement the simple linear regression model for predicting the marks scored.


Developed by:B.Pavizhi 
RegisterNumber: 212221230077


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df=pd.read_csv('/content/student_scores - student_scores.csv')
df.head()
X=df.iloc[:,:-1].values
X
y=df.iloc[:,1].values
y
from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=1/3,random_state=0)
from sklearn.linear_model import LinearRegression
regressor=LinearRegression()
regressor.fit(X_train,y_train)
y_pred=regressor.predict(X_test)
y_pred
y_test
plt.scatter(X_train,y_train,color='violet')
plt.plot(X_train,regressor.predict(X_train),color="black")
plt.title("h vs s (Training Set)")
plt.xlabel("Hours")
plt.ylabel("Scores")
plt.show()
plt.scatter(X_test,y_test,color='purple')
plt.plot(X_test,regressor.predict(X_test),color="black")
plt.title("h vs s (Testing Set)")
plt.xlabel("Hours")
plt.ylabel("Scores")
plt.show()