Marks Prediction of Students in Machine Learning

Program 1

# Machine Learning model for student marks predication
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
from sklearn import linear_model
mydf=pd.read_excel("D://MLFile/result.xlsx")
mymodel=linear_model.LinearRegression()
mymodel.fit(mydf.drop('marks',axis='columns'),mydf.marks)  # Trained Data set
h=float(input("Enter hours for Marks Predication: "))

alpha=mymodel.intercept_
beta=mymodel.coef_
y=alpha+beta*h

os.system('cls')

print(mydf)
print("Predicated Marks :",mymodel.predict([[h]]))
print("Predicated Marks as per Fourmla :",y)
mynewdf=pd.read_excel("D://MLFile/nohours.xlsx")
mymrk=mymodel.predict((mynewdf))
print(mymrk)
mynewdf['Marks']=mymrk
print(mynewdf)
mynewdf.to_excel("D://MLFile/newResult.xlsx")
print("--------Predication done successfully-------------------")