In this project, we will develop and evaluate the performance and the predictive power of a model trained and tested on data collected from India (Bangalore). Linear Regression is applied to analyse historical property transactions. In our case, the house price basically depends on the parameters such as the number of bedrooms, location, size of living area etc. Once we get a good fit, we will use this model to predict the monetary value of a house located at the Bangalore area.
In this project, we will develop and evaluate the performance and the predictive power of a model trained and tested on data collected from India (Bangalore). Linear Regression is applied to analyse historical property transactions. In our case, the house price basically depends on the parameters such as the number of bedrooms, location, size of living area etc. Once we get a good fit, we will use this model to predict the monetary value of a house located at the Bangalore area.
In this project, we will develop and evaluate the performance and the predictive power of a model trained and tested on data collected from India (Bangalore). Linear Regression is applied to analyse historical property transactions. In our case, the house price basically depends on the parameters such as the number of bedrooms, location, size of living area etc. Once we get a good fit, we will use this model to predict the monetary value of a house located at the Bangalore area.