HERE I HAVE TAKEN THE DATASET THROUGH KAGGLE(DATASCIENCE COMPANY) WHICH CONTAINS THE DATA FROM 2014 TO 2018 WE ARE GOING TO CREATE THE MODEL THAT PREDICTS FOR THIS MODEL I HAVE CREATED AN ML AUTO REGRESSION SYSTEM THIS AUTOREGRESSION SYSTEM TAKES THE DATA AND FITS INTO THE REGRESSION BY USING THE FIT FUNCTION AND BEFORE DOIN G THIS WE ARE GOING TO SPLIT THE DATA INTO TRAINING DATA AND TESTING DATA WE GET THE ACCURATE RESULTS FOR THE AUTO REGRESSION SYSTEM THIS IS MY FIRST PROJECT IN ML.
- importing the basic packages such as numpy,pandas,matplotlib.plot 2.importing the dataset into the google collab file by using import files from google function 3.from skilearn importing packages such as logistic regression , label encoder, test train split functions
- plotting the graph for petrol price in chennai
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- assigning X and Y values
- training the data and fitting it into the linaer regression model
- thus we get an graph between predicted price and actual price
- calculating the mean squared eror, root mean squared error and R squared values
- Thus an simple linear regression model to predict the prices of chennai and mumbai have been calcuated and executed sucessfully