This project is a 'Google Solution Challenge Project' on the topic of - Environment. This is our sincere effort to setup a co-operation between mankind and the environment.
A machine learning model created by four tech-savvy undergraduate students.
Read through these lines to know more about me 😃
https://rainpredictor.el.r.appspot.com/
Vasu Arora (Lead)
Simrandeep Singh
Devrajsinh Gohil
Kiran Mishra
India is rich in diversity whether cultural or climatic. Rain is a mandatory phenomenon for us as most of our land is agricultural. Farmers and fishermen are our heroes as they provide us with the necessities for survival. But due to unpredictable rain cycles, most of the farmlands get damaged as the farmers are not ready to handle the untimely rain. Even many fishermen lose their lives as they fail to predict the rains beforehand.We can't lose our food providers to unpredictable climatic changes.
Our project predicts whether it will rain tomorrow or not by using the Rainfall in Australia dataset This project is tested over lot of ml models like catboost, xgboost, random forest, support vector classifier, etc.Out of these models catboost performed very well giving an AUC score around and ROC score of 89 far better than others.We didn't get any dataset related to Indian rainfall on Kaggle,so we went on with the Australian data to train our model.
📍 Front-End : HTML, CSS, Bootstrap
📍 Back-End : Flask
📍 IDE : Jupyter notebook, Visual Studio Code
📍 Dataset used : (link)
🌱 As you tap on the link to our site, you will get to see the 'About' section and a little bit about us.
🌱Select the 'Predictor' option and fill in the details like Date, Maximum temperature, Minimum temperature, rainfall, evaporation and the rest.
🌱 Take special care in selecting the Location.
🌱 In just few seconds you will get 89% accurate prediction about the next day's rainfall.
