{"id":26120572,"url":"https://github.com/gunjangyl/rainfall_prediction_system","last_synced_at":"2026-04-20T15:31:43.636Z","repository":{"id":281521016,"uuid":"933289237","full_name":"gunjangyl/Rainfall_Prediction_System","owner":"gunjangyl","description":"The Rainfall Prediction System is a machine learning-based web application that forecasts rainfall based on weather parameters like precipitation, temperature, and wind speed. ","archived":false,"fork":false,"pushed_at":"2025-04-17T14:49:47.000Z","size":59,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-18T05:28:52.137Z","etag":null,"topics":["bootstrap","css","django","html","javascript","jupyter-notebook","numpy","pandas","python"],"latest_commit_sha":null,"homepage":"http://127.0.0.1:8000/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/gunjangyl.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-02-15T15:55:02.000Z","updated_at":"2025-04-17T14:49:51.000Z","dependencies_parsed_at":null,"dependency_job_id":"ee8619f9-56da-4095-8d40-277bb2287b80","html_url":"https://github.com/gunjangyl/Rainfall_Prediction_System","commit_stats":null,"previous_names":["gunjangyl/rainfall_prediction_system"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/gunjangyl/Rainfall_Prediction_System","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gunjangyl%2FRainfall_Prediction_System","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gunjangyl%2FRainfall_Prediction_System/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gunjangyl%2FRainfall_Prediction_System/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gunjangyl%2FRainfall_Prediction_System/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gunjangyl","download_url":"https://codeload.github.com/gunjangyl/Rainfall_Prediction_System/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gunjangyl%2FRainfall_Prediction_System/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32053179,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T11:35:06.609Z","status":"ssl_error","status_checked_at":"2026-04-20T11:34:48.899Z","response_time":94,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["bootstrap","css","django","html","javascript","jupyter-notebook","numpy","pandas","python"],"created_at":"2025-03-10T13:43:12.186Z","updated_at":"2026-04-20T15:31:43.631Z","avatar_url":"https://github.com/gunjangyl.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Rainfall_Prediction_System\n\n## 📖 Overview\nThe Rainfall Prediction System is a machine learning-based project designed to predict rainfall using meteorological data. It leverages various machine learning models to analyze factors such as temperature, humidity, wind speed, and atmospheric pressure to estimate rainfall probability.\n\n## 📌 Features\n- ✅ Data Preprocessing \u0026 Cleaning\n- ✅ Exploratory Data Analysis (EDA)\n- ✅ Machine Learning Models (Linear Regression, Random Forest, etc.)\n- ✅ Model Evaluation \u0026 Performance Metrics\n- ✅ Web Interface (Optional for deployment)\n\n## 🏗️ Technologies Used\n- **Programming Language**: Python\n- **Libraries**: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn\n- **Jupyter Notebook** for analysis \u0026 model training\n- **Flask (Optional)** for deploying a web interface\n\n## 📊 Dataset\nThe dataset includes various meteorological parameters such as:\n- 🌡️ Temperature\n- 💧 Humidity\n- 💨 Wind Speed\n- 🔽 Pressure\n- 🌧️ Precipitation\n\n## 🔧 Installation \u0026 Setup\n1️⃣ Clone the repository:\n```bash\ngit clone https://github.com/gunjangyl/Rainfall_Prediction_System.git\ncd Rainfall_Prediction_System\ncd myproject\n```\n\n2️⃣ Install dependencies:\n```bash\npip install -r requirements.txt\n```\n\n3️⃣ Run the system:\n```bash\npython mmanage.py runserver\n```\n\n## 🏋️‍♂️ Model Training\nTo train the model, run:\n```bash\npython src/train_model.py\n```\nThis will process the dataset and train the model using selected algorithms.\n\n## 📜 Results\n- Model accuracy: **85-90%** (may vary based on dataset and parameters)\n- Evaluation Metrics: Mean Squared Error (MSE), R-Squared, etc.\n- Visualization of feature importance and model predictions.\n\u003cbr\u003e\u003cbr\u003e\n\n## DEMONSTRATION\n\u003cbr\u003e\u003cbr\u003e\n\u003cb\u003eRainfall Prediction Dashboard\u003cb\u003e\n![Image](https://github.com/user-attachments/assets/bb8fc660-ed31-4e48-9ef0-465745d2b5cf)\n\u003cbr\u003e\u003cbr\u003e\n\u003cb\u003eUser Input Page(For Input Data Example 1)\u003c/b\u003e\n![Image](https://github.com/user-attachments/assets/b18831fb-7f24-4b41-bfe6-9dcd0fe8d6c7)\n\u003cbr\u003e\u003cbr\u003e\n\u003cb\u003eForecast Output Page\u003c/b\u003e\n![Image](https://github.com/user-attachments/assets/dbe8c05b-d105-4e25-bccf-d5fea2f23e1b)\n\u003cbr\u003e\u003cbr\u003e\n\u003cb\u003eUser Input Page(For Input Data Example 2)\u003c/b\u003e\n![Image](https://github.com/user-attachments/assets/cc4cd55f-a76c-4078-bb0b-02f88df5d339)\n\u003cbr\u003e\u003cbr\u003e\n\u003cb\u003eForecast Output Page\u003c/b\u003e\n![Image](https://github.com/user-attachments/assets/8ff46df3-f555-475a-aa47-5eff8d29a1b6)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgunjangyl%2Frainfall_prediction_system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgunjangyl%2Frainfall_prediction_system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgunjangyl%2Frainfall_prediction_system/lists"}