https://github.com/jiteshshelke/weather-type-classification-webapp
🌦️ A Flask-based ML web app for classifying weather types (Sunny, Rainy, Cloudy, Snowy) using multiple models. ⛅⚡❄️
https://github.com/jiteshshelke/weather-type-classification-webapp
ai classification data-science decision-trees deep-learning flask iot knn logistic-regression machine-learning ml-models predictive-modeling python random-forest support-vector-machines weather weather-classification weather-forecast
Last synced: about 1 month ago
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🌦️ A Flask-based ML web app for classifying weather types (Sunny, Rainy, Cloudy, Snowy) using multiple models. ⛅⚡❄️
- Host: GitHub
- URL: https://github.com/jiteshshelke/weather-type-classification-webapp
- Owner: JiteshShelke
- License: mit
- Created: 2025-03-31T06:04:59.000Z (about 1 month ago)
- Default Branch: master
- Last Pushed: 2025-03-31T06:47:37.000Z (about 1 month ago)
- Last Synced: 2025-03-31T07:24:48.443Z (about 1 month ago)
- Topics: ai, classification, data-science, decision-trees, deep-learning, flask, iot, knn, logistic-regression, machine-learning, ml-models, predictive-modeling, python, random-forest, support-vector-machines, weather, weather-classification, weather-forecast
- Language: Jupyter Notebook
- Homepage:
- Size: 4.23 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Support: Support Vector Machine.pkl
Awesome Lists containing this project
README
# 🌦️ Weather Type Classification WebApp
## 🚀 Overview
A machine learning-powered web application for predicting weather types based on various atmospheric conditions. Built using Flask and multiple ML models, this app classifies weather into **Rainy ☔, Cloudy ☁️, Sunny ☀️, and Snowy ❄️**.
## 🏗️ Features
- ✅ Uses Logistic Regression, Decision Tree, Random Forest, SVM, and KNN models.
- ✅ Web-based interface built with Flask & HTML/CSS.
- ✅ User-friendly input form for weather parameters.
- ✅ Real-time predictions.
- ✅ Interactive UI with weather-themed pages.
## 🖼️ Screenshots
| Home Page | Prediction Output |
|-----------|------------------|
|  |  |
## 🛠️ Tech Stack
- **Frontend:** HTML, CSS, JavaScript
- **Backend:** Flask
- **Machine Learning:** Scikit-Learn, Joblib, Pandas, NumPy
## 📂 Folder Structure
```
📦 Weather-Type-Classification-WebApp
├── 📂 static # CSS, JS, and images
├── 📂 templates # HTML files (home, results pages)
├── models # Saved ML models (joblib/pickle format)
├── app.py # Flask application
├── requirements.txt # Dependencies
└── README.md # Project documentation
```
## 🔧 Installation & Usage
### 1️⃣ Clone the Repository
```sh
git clone https://github.com/yourusername/Weather-Type-Classification-WebApp.git
cd Weather-Type-Classification-WebApp
```
### 2️⃣ Install Dependencies
```sh
pip install -r requirements.txt
```
### 3️⃣ Run the Application
```sh
python app.py
```
**Open the browser and go to:** `http://127.0.0.1:5000/`
## 🎯 How It Works
1. Enter weather-related inputs in the web form.
2. Click "Predict" to classify the weather type.
3. The app displays the predicted weather category.
## 🛠️ Model Training
- The dataset is preprocessed and split into training and testing sets.
- Different ML models are trained, and the best-performing model is selected.
- The selected model is saved using `joblib`.
## 🏆 Results & Accuracy
| Model | Accuracy |
|--------|----------|
| Logistic Regression | 85% |
| Decision Tree | 88% |
| Random Forest | 92% |
| SVM | 90% |
| KNN | 87% |
## 🤝 Contribution
Contributions are welcome! Please follow these steps:
1. Fork the repository.
2. Create a new branch.
3. Commit your changes.
4. Open a Pull Request.
## 📜 License
This project is licensed under the **MIT License**.
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Made with ❤️ by Jitesh Shelke