Home Price Prediction Model

The Home Price Prediction Model is hosted on this IP:

Basic workflow is:

  1. Machine learning model is trained on previous available data which contains multiple houses’ features and price each house eventually sold for
  2. Trained and tested machine learning model is uploaded to a server
  3. Front-end of the website is built using Flask, HTML and CSS, and now custom house features, controlled by the user, are able to be passed directly to the backend and fed into the model for prediction
  4. Model receives inputs, and produces a prediction (approximation) of how much a house with features provided would sell for. 
  5. Predicted sales price of the house is then displayed on the page.

Detailed description of the project to follow shortly.