Thrive

Objectives

• To develop a model that can predict whether it will rain tomorrow.
• To allow researchers to control extraneous factors.
• To test the relationship between one dependent variable and many independent variables.
• To create a decision making tool in order to perform day-to-day activities in the lifes of a normal being, farmer or any other.

Technical aspects used in this project are :

• Machine Learning (ML)
• Logistic regression in ML
• XGBoost
• Gaussian naive Bayes
• Bernoulli naive Bayes
• Random forest
• Dashboard creation using Data Visualization
• Flask
• Tableau

Findings -

The highest accuracy is attained by the technique, Random Forest with an accuracy of 90.66%.

Dashboard -

Click here to view our Tableau dashboard -

https://public.tableau.com/views/thrive/Weather_data_analysis?:language=en&:display_count=y&publish=yes&:origin=viz_share_link/