This is the project contains the data set and the code for predicting the price of house based on various of its feature like no of bedrooms, size, society, total_sqft, bath, balcony etc.
Firstly, import both the files in the colab environment.
The data is firstly preprocesed by importing , cleaning and filling the null values. Then the unnecessary columns are removed from the training dataset The data is then split and passes to the linear regression model and the model is trained.
The code also includes a database generator for generating random prices to train the model.
Lastly, the predictor is enabled and based upon the values , the price is returned by the program.
https://colab.research.google.com/drive/1uVqGM6HbsYBvS3h44pwSORFoQK5aOKLx?usp=sharing