{"id":51221119,"url":"https://github.com/sankhya007/winter-internship-projects-2025","last_synced_at":"2026-06-28T07:03:54.027Z","repository":{"id":324959630,"uuid":"1099242016","full_name":"sankhya007/winter-internship-projects-2025","owner":"sankhya007","description":null,"archived":false,"fork":false,"pushed_at":"2025-11-18T20:39:06.000Z","size":4066,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-11-18T21:05:56.247Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","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/sankhya007.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-11-18T18:47:25.000Z","updated_at":"2025-11-18T20:39:09.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/sankhya007/winter-internship-projects-2025","commit_stats":null,"previous_names":["sankhya007/winter-internship-projects-2025"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/sankhya007/winter-internship-projects-2025","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sankhya007%2Fwinter-internship-projects-2025","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sankhya007%2Fwinter-internship-projects-2025/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sankhya007%2Fwinter-internship-projects-2025/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sankhya007%2Fwinter-internship-projects-2025/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sankhya007","download_url":"https://codeload.github.com/sankhya007/winter-internship-projects-2025/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sankhya007%2Fwinter-internship-projects-2025/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34880199,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-28T02:00:05.809Z","response_time":54,"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":[],"created_at":"2026-06-28T07:03:53.439Z","updated_at":"2026-06-28T07:03:54.018Z","avatar_url":"https://github.com/sankhya007.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Winter Internship Projects 2025\r\n\r\n## Project 1: Housing Data Analysis with Python\r\n\r\n### 📊 Project Description\r\nComplete data analysis of California housing dataset using Pandas and Matplotlib as per internship requirements.\r\n\r\n### ✅ Tasks Completed\r\n- Loaded CSV file using Pandas library\r\n- Performed basic data analysis and calculated averages\r\n- Created visualizations: Bar charts, Scatter plots, Heatmaps\r\n- Provided detailed insights and observations\r\n\r\n### 🛠 Technologies Used\r\n- Python\r\n- Pandas\r\n- NumPy\r\n- Matplotlib\r\n- Scikit-learn\r\n\r\n### 📁 Files\r\n- `complete_analysis.py` - Basic data analysis code\r\n- `housing.csv` - Dataset\r\n- `requirements.txt` - Dependencies\r\n- `README.md` - Project documentation\r\n\r\n### 🚀 How to Run\r\n1. Install dependencies: `pip install -r requirements.txt`\r\n2. Run analysis: `python complete_analysis.py`\r\n\r\n---\r\n\r\n## Project 2: House Price Prediction using Linear Regression\r\n\r\n### 🏠 Advanced House Price Prediction System\r\n\r\nA comprehensive machine learning project that predicts California\r\nhousing prices using multiple regression algorithms with advanced\r\nfeature engineering and visualization.\r\n\r\n### 📊 Project Overview\r\n\r\nThis project implements an end-to-end machine learning pipeline for\r\npredicting median house values in California districts. The system\r\nincludes advanced data preprocessing, feature engineering, multiple\r\nmodel comparison, and comprehensive visualization.\r\n\r\n### 🚀 Features\r\n\r\n-   Advanced Data Preprocessing: Automated missing value imputation and\r\n    data validation\r\n-   Feature Engineering: Created interaction features, location-based\r\n    metrics, and categorical encoding\r\n-   Multiple Algorithms: Linear Regression, Ridge, Lasso, and Random\r\n    Forest\r\n-   Model Comparison: Comprehensive evaluation with cross-validation\r\n-   Advanced Visualizations: Interactive charts and business\r\n    intelligence reports\r\n-   Feature Importance: Detailed analysis of price drivers\r\n-   Confidence Intervals: Prediction ranges with statistical confidence\r\n\r\n\r\n### 🛠️ Installation\r\n\r\n1.  Clone the repository:\r\n    ```bash\r\n    git clone https://github.com/yourusername/house-price-prediction.git\r\n    cd house-price-prediction\r\n    Install dependencies:\r\n\r\n    bash\r\n    pip install -r requirements.txt\r\n    Ensure you have the housing.csv dataset in the project root.\r\n\r\n### 🎯 Usage\r\n\r\nRun the main script:\r\n\r\n    python linear_regression_model.py\r\n\r\nThe script will:\r\n\r\n-   Load and validate the dataset\r\n-   Perform advanced preprocessing and feature engineering\r\n-   Train multiple machine learning models\r\n-   Generate comprehensive visualizations\r\n-   Provide business insights and predictions\r\n\r\n### 📈 Model Performance\r\n\r\nThe system compares multiple algorithms:\r\n\r\n-   Linear Regression: Baseline performance\r\n-   Ridge Regression: Regularized linear model\r\n-   Lasso Regression: Feature selection capabilities\r\n-   Random Forest: Ensemble tree-based approach\r\n\r\n### 🔍 Key Insights\r\n\r\n-   Identifies top price-driving features\r\n-   Provides confidence intervals for predictions\r\n-   Generates strategic business recommendations\r\n-   Visualizes model performance and data relationships\r\n\r\n### 📊 Sample Predictions\r\n\r\nThe system includes pre-configured property profiles:\r\n\r\n-   Luxury Coastal Villa: High-end properties\r\n-   Family Suburban Home: Middle-income housing\r\n-   Investment Opportunity: Value properties\r\n\r\n### 🧪 Technical Details\r\n\r\nDataset: California Housing Prices (20,640 samples, 10 features)\r\n\r\nPreprocessing: StandardScaler, VarianceThreshold, SimpleImputer\r\n\r\nValidation: 80-20 train-test split, 3-fold cross-validation\r\n\r\nMetrics: R² Score, MAE, RMSE, Cross-validation scores\r\n\r\n\r\n\r\n## Project 3: Matrix Operations Tool\r\n\r\nA comprehensive Python application for performing various matrix\r\noperations using NumPy. Features an interactive command-line interface\r\nfor easy matrix manipulation and analysis.\r\n\r\n### Features\r\n\r\n-   Matrix Input: Interactive matrix input with validation\r\n-   Basic Operations: Addition, Subtraction, Multiplication\r\n-   Advanced Operations: Transpose, Determinant, Inverse\r\n-   Matrix Management: Store, view, and delete multiple matrices\r\n-   Error Handling: Comprehensive input validation and error messages\r\n-   Demo Mode: Preloaded matrices for quick testing\r\n\r\n### Operations Supported\r\n\r\n1.  Matrix Addition\r\n2.  Matrix Subtraction\r\n3.  Matrix Multiplication\r\n4.  Matrix Transpose\r\n5.  Matrix Determinant\r\n6.  Matrix Inverse\r\n7.  Input New Matrix\r\n8.  View All Matrices\r\n9.  Delete Matrix\r\n\r\n### Installation\r\n\r\n1.  Ensure you have Python installed on your system.\r\n2.  Install the required dependency:\r\n\r\n    pip install numpy\r\n\r\n3.  Run the application:\r\n\r\n    python matrix_operation.py\r\n\r\n### Usage\r\n\r\n-   Start the application and choose whether to load demo matrices.\r\n-   Use the menu to perform operations:\r\n    -   First, input matrices using option 7.\r\n    -   Then perform operations like addition, multiplication, etc.\r\n-   View results in formatted output.\r\n-   Results are automatically stored for further operations.\r\n\r\n### Project Structure\r\n\r\nmatrix_operation_tools/ - matrix_operation.py - housing.csv - README.md\r\n\r\n### Technical Details\r\n\r\n-   Built With: Python, NumPy\r\n-   Architecture: Object-oriented design\r\n-   Error Handling: Comprehensive validation\r\n-   UI: Clean command-line interface\r\n\r\n### 🤝 Contributing\r\n\r\n-   Fork the project\r\n-   Create your feature branch (git checkout -b feature/AmazingFeature)\r\n-   Commit your changes (git commit -m ‘Add some AmazingFeature’)\r\n-   Push to the branch (git push origin feature/AmazingFeature)\r\n-   Open a Pull Request\r\n\r\n### 📄 License\r\n\r\nThis project is licensed under the MIT License - see the LICENSE file\r\nfor details.\r\n\r\n### 👥 Authors\r\n\r\n- **Sankhyapriyo Dey** - *Initial work* - [sankhya007](https://github.com/sankhya007)\r\n\r\n### 🙏 Acknowledgments\r\n\r\n-   Dataset sourced from California Housing Prices\r\n-   Scikit-learn for machine learning algorithms\r\n-   Matplotlib and Seaborn for visualizations\r\n\r\n-   png image visualization \r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsankhya007%2Fwinter-internship-projects-2025","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsankhya007%2Fwinter-internship-projects-2025","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsankhya007%2Fwinter-internship-projects-2025/lists"}