/*
Program to implement the simple linear regression model for predicting the marks scored.
Developed by: Syed Abdul Wasih H
Register Number:  212221240057
*/
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
dataset = pd.read_csv('Stud_scores.csv')
dataset.head()
X = dataset.iloc[:,:-1].values
X
Y = dataset.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="purple")
plt.plot(X_train,regressor.predict(X_train),color="black")
plt.title("Hours vs Scores (Training Set)")
plt.xlabel("Hours")
plt.ylabel("Scores")
plt.show()
plt.scatter(X_test,Y_test,color="red")
plt.plot(X_train,regressor.predict(X_train),color="black") 
plt.xlabel("Hours")
plt.ylabel("Scores")
plt.show()