It is a machine learning model which predicts the house price in Bangalore.
This model is trained using a dataset that contains information about 13321 houses. However, this dataset has a lot of missing values and features containing nonnumerical values. So initially the dataset was not suitable for direct use.
An exploratory data analysis is performed for making the dataset suitable for feeding the algorithm. A multivariate linear regression machine learning algorithm is used in this model and an accuracy of 94.36% is found.
It is a machine learning model which predicts the house price in Bangalore.
This model is trained using a dataset that contains information about 13321 houses. However, this dataset has a lot of missing values and features containing nonnumerical values. So initially the dataset was not suitable for direct use.
An exploratory data analysis is performed for making the dataset suitable for feeding the algorithm. A multivariate linear regression machine learning algorithm is used in this model and an accuracy of 94.36% is found.