What are the things that a potential home buyer considers before purchasing a house? The location, the size of the property, schools, parks, restaurant, hospitals, etc. What about the most important factor -- the price?
The End-goal of this project is to give an estimate of how much prices a house will have on the basis of features like Size of a House, Location and etc.
There are 9 features and each feature can be accessed by its name.
- Area_type - describes the area
- Availability - when it can be possessed or when it is ready(categorical and time-series)
- Location - where it is located in Bengaluru
- Size - in BHK or Bedroom (1-10 or more)
- Society - to which society it belongs
- Total_sqft - size of the property in sq.ft
- Bath - No. of bathrooms
- Balcony - No. of the balcony
- Price - Value of the property in lakhs(INR)
This 9 features(categorical and continuous) is used to build a model to predict the price of houses in Bengaluru.
Libraries: Python Numpy Pandas matplotlib sklearn
Categorical variable Distribution
Correlation Plot
EDA
ML Regression
Regression Metrics
If you have any feedback, please reach out at goplaljadhav061.gj@gmail.com
I am an Data science Enthusiast and ML practitioner
