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Machine Learning model to predict price_of_house


Today let's look at one of the machine learning model which can predict the prices of house based on the described data.

We'll look at the linear regression model for which we'll follow a few steps such as:

  1. import required modules
  2. read the csv file
  3. plot the graph
  4. building the linear regression model to fit/train the data
  5. predict value with a parameter
  6. have a new data file for value prediction
(to view the images either open it in a new tab or zoom-in please!)
Let's start coding:

1. import required modules




2. read the csv file: (open this image in new tab)



    So, we have this data: (open this image in new tab)


3. plot the graph


4. building the linear regression model to fit/train the data



5. predict value with a parameter



6. have a new data file for value prediction


And thus, we get the output for the "newdata" file here in the form of an array.



Hence, we add a new column to our "newdata" dataframe as 'price'.



And we can plot the graph for "newdata" dataframe as follows:


We can also save this newdata dataframe to csv: (open this image in new tab)


And this is how we can predict values for the given parameter.



I'm providing the github link here for your reference: github

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