{"id":26873602,"url":"https://github.com/jiteshshelke/weather-type-classification-webapp","last_synced_at":"2026-04-20T09:33:57.584Z","repository":{"id":285341652,"uuid":"957786586","full_name":"JiteshShelke/Weather-Type-Classification-WebApp","owner":"JiteshShelke","description":"🌦️ A Flask-based ML web app for classifying weather types (Sunny, Rainy, Cloudy, Snowy) using multiple models. ⛅⚡❄️","archived":false,"fork":false,"pushed_at":"2025-03-31T06:47:37.000Z","size":4434,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-31T07:24:48.443Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/JiteshShelke.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":"Support Vector Machine.pkl","governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-31T06:04:59.000Z","updated_at":"2025-03-31T06:47:40.000Z","dependencies_parsed_at":"2025-03-31T07:34:53.107Z","dependency_job_id":null,"html_url":"https://github.com/JiteshShelke/Weather-Type-Classification-WebApp","commit_stats":null,"previous_names":["jiteshshelke/weather-type-classification-webapp"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/JiteshShelke/Weather-Type-Classification-WebApp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JiteshShelke%2FWeather-Type-Classification-WebApp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JiteshShelke%2FWeather-Type-Classification-WebApp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JiteshShelke%2FWeather-Type-Classification-WebApp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JiteshShelke%2FWeather-Type-Classification-WebApp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JiteshShelke","download_url":"https://codeload.github.com/JiteshShelke/Weather-Type-Classification-WebApp/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JiteshShelke%2FWeather-Type-Classification-WebApp/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269693593,"owners_count":24460248,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-10T02:00:08.965Z","response_time":71,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["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"],"created_at":"2025-03-31T09:19:37.387Z","updated_at":"2026-04-20T09:33:57.505Z","avatar_url":"https://github.com/JiteshShelke.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🌦️ Weather Type Classification WebApp\n\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/Made%20with-Python-blue?style=for-the-badge\u0026logo=python\" /\u003e\n  \u003cimg src=\"https://img.shields.io/badge/Built%20with-Love-red?style=for-the-badge\" /\u003e\n  \u003cimg src=\"https://img.shields.io/badge/Uses-Flask-green?style=for-the-badge\u0026logo=flask\" /\u003e\n\u003c/p\u003e\n\n\n## 🚀 Overview\nA 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 ❄️**.\n\n## 🏗️ Features\n- ✅ Uses Logistic Regression, Decision Tree, Random Forest, SVM, and KNN models.\n- ✅ Web-based interface built with Flask \u0026 HTML/CSS.\n- ✅ User-friendly input form for weather parameters.\n- ✅ Real-time predictions.\n- ✅ Interactive UI with weather-themed pages.\n\n## 🖼️ Screenshots\n| Home Page | Prediction Output |\n|-----------|------------------|\n| ![Home](./images/1.png) | ![Result](./images/2.png) |\n\n## 🛠️ Tech Stack\n- **Frontend:** HTML, CSS, JavaScript\n- **Backend:** Flask\n- **Machine Learning:** Scikit-Learn, Joblib, Pandas, NumPy\n\n## 📂 Folder Structure\n```\n📦 Weather-Type-Classification-WebApp\n├── 📂 static        # CSS, JS, and images\n├── 📂 templates     # HTML files (home, results pages)\n├── models       # Saved ML models (joblib/pickle format)\n├── app.py          # Flask application\n├── requirements.txt # Dependencies\n└── README.md       # Project documentation\n```\n\n## 🔧 Installation \u0026 Usage\n### 1️⃣ Clone the Repository\n```sh\ngit clone https://github.com/yourusername/Weather-Type-Classification-WebApp.git\ncd Weather-Type-Classification-WebApp\n```\n### 2️⃣ Install Dependencies\n```sh\npip install -r requirements.txt\n```\n### 3️⃣ Run the Application\n```sh\npython app.py\n```\n**Open the browser and go to:** `http://127.0.0.1:5000/`\n\n## 🎯 How It Works\n1. Enter weather-related inputs in the web form.\n2. Click \"Predict\" to classify the weather type.\n3. The app displays the predicted weather category.\n\n## 🛠️ Model Training\n- The dataset is preprocessed and split into training and testing sets.\n- Different ML models are trained, and the best-performing model is selected.\n- The selected model is saved using `joblib`.\n\n## 🏆 Results \u0026 Accuracy\n| Model | Accuracy |\n|--------|----------|\n| Logistic Regression | 85% |\n| Decision Tree | 88% |\n| Random Forest | 92% |\n| SVM | 90% |\n| KNN | 87% |\n\n## 🤝 Contribution\nContributions are welcome! Please follow these steps:\n1. Fork the repository.\n2. Create a new branch.\n3. Commit your changes.\n4. Open a Pull Request.\n\n## 📜 License\nThis project is licensed under the **MIT License**.\n\n---\n\u003cp align=\"center\"\u003eMade with ❤️ by \u003ca href=\"https://github.com/JiteshShelke\"\u003eJitesh Shelke\u003c/a\u003e\u003c/p\u003e\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjiteshshelke%2Fweather-type-classification-webapp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjiteshshelke%2Fweather-type-classification-webapp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjiteshshelke%2Fweather-type-classification-webapp/lists"}