Machine learning based approach for predicting house price in real estate.

The proposed application must assist a targeted user to obtaining real estate property information with elegant correctness and precise output. By implementing the proposed algorithmic prediction process, which will forecast various property prices based on several criterions. We're going to use datasets from the landmark we're going to forecast, and this landmark can be changed according to the area we want to predict. We'll use a linear regression technique to predict, and by utilizing Flask framework more accurate results can be acquired. We discovered that by training data to the maximum, we were able to achieve absolute outcomes. We can forecast working in this subject by leveraging technologies such as Python, which allows us to train and collect more entertaining data. In comparison to other investments, real estate property prices are unaffordable. We can say that we are able to predict. [ABSTRACT FROM AUTHOR]

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