https://github.com/theanujsinha01/rainfall-prediction-using-machine-learning
This project predicts whether it will rain or not based on weather features like pressure, humidity, dew point, cloud cover, sunshine, wind direction, and wind speed. We use a Random Forest Classifier, a popular ML algorithm, trained on historical weather data. The model learns patterns and helps us forecast rain chances.
https://github.com/theanujsinha01/rainfall-prediction-using-machine-learning
classification data-analysis eda machine-learning-algorithms matplotlib numpy pandas python scikit-learn seaborn supervised-learning
Last synced: 7 months ago
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This project predicts whether it will rain or not based on weather features like pressure, humidity, dew point, cloud cover, sunshine, wind direction, and wind speed. We use a Random Forest Classifier, a popular ML algorithm, trained on historical weather data. The model learns patterns and helps us forecast rain chances.
- Host: GitHub
- URL: https://github.com/theanujsinha01/rainfall-prediction-using-machine-learning
- Owner: theanujsinha01
- Created: 2025-06-27T07:30:43.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-06-27T07:39:46.000Z (7 months ago)
- Last Synced: 2025-06-27T08:35:08.387Z (7 months ago)
- Topics: classification, data-analysis, eda, machine-learning-algorithms, matplotlib, numpy, pandas, python, scikit-learn, seaborn, supervised-learning
- Language: Jupyter Notebook
- Homepage: https://rainfall-prediction-using-machine-learning.streamlit.app/
- Size: 370 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Rainfall-Prediction-Using-Machine-Learning
This project predicts whether it will rain or not based on weather features like pressure, humidity, dew point, cloud cover, sunshine, wind direction, and wind speed. We use a Random Forest Classifier, a popular ML algorithm, trained on historical weather data. The model learns patterns and helps us forecast rain chances.
This project is a **web-based application** that predicts whether it will rain today based on real-world weather input features like pressure, humidity, cloud cover, sunshine, etc. It uses a **Random Forest Classifier** trained on historical weather data and is deployed as an interactive **Streamlit app**.
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## Live : https://rainfall-prediction-using-machine-learning.streamlit.app/
## 📌 Problem Statement
Predicting rainfall is crucial in weather forecasting. It helps:
- Farmers plan irrigation and harvesting.
- People manage daily travel plans.
- Cities prepare for flood alerts or water conservation.
Traditional methods require large infrastructure, but machine learning can make accurate predictions from past weather patterns.
---
## 🎯 Objective
To build a machine learning model that:
- Takes weather features as input.
- Predicts whether it will rain or not.
- Provides results through a simple and user-friendly web app.
---
## 📊 Features of the App
✅ Predicts Rain or No Rain
✅ Easy-to-use UI built with **Streamlit**
✅ Takes 7 weather parameters as input
✅ Displays prediction with icons: ☀️ / 🌧️
✅ Trained using **Random Forest Classifier**
✅ Model saved and loaded using **joblib**
---
## 🧪 Input Features Used for Prediction
| Feature | Description |
|----------------|-------------------------------|
| `pressure` | Atmospheric pressure (hPa) |
| `dewpoint` | Dew point temperature (°C) |
| `humidity` | Relative humidity (%) |
| `cloud` | Cloud cover (%) |
| `sunshine` | Sunshine duration (hours) |
| `winddirection` | Wind direction in degrees (°) |
| `windspeed` | Wind speed in km/h |
---
## 🧠 Machine Learning Model
- **Algorithm Used**: `RandomForestClassifier` (from Scikit-learn)
- **Model Training Steps**:
- Data Preprocessing
- Train-Test Split
- Feature Selection
- Model Tuning with GridSearchCV
- **Evaluation Metrics**:
- Accuracy
- Confusion Matrix
- Classification Report
- **Model Deployment**:
- Saved as `.pkl` file using `joblib`
- Loaded into the Streamlit app for prediction
---
## 🛠️ Tech Stack
| Tool/Library | Purpose |
|----------------|-------------------------------|
| Python | Programming Language |
| Pandas & NumPy | Data handling and processing |
| Scikit-learn | Machine Learning model |
| Matplotlib & Seaborn | Data Visualization |
| Joblib | Model saving/loading |
| Streamlit | Web App frontend |
---