Meadow

Green Scope Predictor

Machine Learning Project
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About The Project

• Using Data Science and Machine learning, we built a website that can calculate the green score of a plot of land. The Green Score of a land, for now, only takes two parameters: the water table and the market trend values, to calculate how feasible the land is on a score of 1 - 10.
• Pandas, Numpy, Matplotlib for csv reading, Data Processing, Data Cleaning, Visualization etc.

Deployed website

Introduction

• There are two datasets used in this project: Ames Housing Dataset and Rainfall dataset; for calculating the market trend value and the rainfall of a particular place.
• We predict future market trends and estimate the current market value of the land using a trained Convolutional Neural Network (CNN) model. This model will analyze factors such as land area, quality, and previous sale prices to determine the market value.
• We predict the water table level based on rainfall data and historical environmental patterns using a CNN model. The model will provide insights into water availability, which is crucial for agricultural or residential planning.
• The data from above two is fed into a final CNN model that calculates the final green score of a place on a scale of 1-10.

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Technologies used

Members:

Bhavana PH Neema Vinod Samridhi Singh