In reviewing the real estate industry, it is evident that numerous customers grapple with a sense of being overwhelmed and dissatisfied. This dissatisfaction is a direct consequence of the sector's inefficiencies and stagnation in terms of innovation, leading to confusion, delays and dissatisfaction among buyers, sellers and agents utilizing traditional methods.
The first and foremost challenge was to predict the complexities and trends that the Real Estate market owns.
As, when we have started our project we decided to follow the revolutionary themes and innovative ideas that could be implemented in the industry in order to get the best outcome of it.
The project followed many stages during its building and handeling process such as; fetching data that is required to combine and train the algorithms for "Future Rate Predictions, "Data Fetching from the trusted sources" & "Generating and Extracting the API keys.
Some more mini bugs and problems were coming during the project but our team somehow manges to fix the bugs and erors that were happening during the project building and We responded to the complex things very approachably and got the solution that is more user friendly and which is more optimised than the previous one.
We found the above mentioned problems and then we started to get over of it by one by one ;
We fetch the data using "web scrapping", and predict the future Rate/Price of the Property using the LSTM and RNN concepts of Deep Learning.
Long short-term memory is an artificial neural network used in the fields of artificial intelligence and deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. Such a recurrent neural network can process not only single data points, but also entire sequences of data.
By the end of it we manages to produce all the working features and add on features of the android application that we build which is named as "PropertEz".
Tracks Applied (2)
Polygon
ETHIndia
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