Rainfall Prediction using Machine Learning

This project predicts whether rainfall will occur based on meteorological data using a machine learning classification model.

Overview

Rainfall prediction is an important aspect of weather forecasting that helps in planning agricultural activities, disaster management, and water resource management. In this project, a classification model is trained on weather data to predict rainfall.

Algorithms Used

• Logistic Regression
• Decision Tree
• Random Forest
• Support Vector Machine

Dataset

• Data from https://1drv.ms/x/c/2b0ffd83beaaf2d2/EQCiQYFMedRKq1_P2Tc3LCwBwTZgxsEr1oWYPo15duh1ZQ?e=IuwLWO
• Features include:
  • Temperature
  • Humidity
  • Wind speed
  • Rain Today
  • Rain Tomorrow (Target)

Tech Stack

• Python
• Pandas, NumPy
• scikit-learn
• Matplotlib, Seaborn (for visualization)

How to Run

1. Clone the repo:

git clone https://github.com/Bhupendra-glitch/Rainfall-Prediction.git

2.Install dependencies

pip install -r requirements.txt

3. Run the Jupyter notebook:

jupyter notebook Rainfall-Prediction.ipynb