Property price prediction using data science and Machine learning
Real Estate Purchase is a popular investment performed on a global level. People while searching for a property look for various features associated with it such as location, number of rooms, bathrooms, square feet area etc. But they are not sure about how these features effect the price of a house for a particular location and thus, they are unable to estimate a correct price for selling or buying the property.
Most metropolitan cities which are fully organized have the data of their real estate well maintained and easily accessible. Ghaziabad, being a semi-urban city, does not have a very well-maintained collection of its real estate data.
Thus, it becomes difficult for a buyer or a seller in Ghaziabad to analyze the data, in order to predict the market price of the current scenario.
The aim of the project is –
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To analyze the properties in Ghaziabad for different regions, based on parameters such as number of rooms , size , bathrooms etc. From different websites and then scraping relevant information from them to form a Robust dataset.
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To successfully apply Data Science tools to refine the dataset further in order to achieve consistency in the data.
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To implement the Machine Learning and finding the best regression model by successfully feeding the dataset to the program.
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To deliver a user-friendly website which would predict the price of property based on the features specified by the user.