{"id":23340279,"url":"https://github.com/zen204/airbnb-availability","last_synced_at":"2026-01-21T01:02:02.089Z","repository":{"id":253580640,"uuid":"843925980","full_name":"Zen204/airbnb-availability","owner":"Zen204","description":"A machine learning model that predicts Airbnb listing availability, utilizing feature engineering and supervised learning techniques to improve guest experience and optimize host management.","archived":false,"fork":false,"pushed_at":"2024-12-26T06:35:05.000Z","size":23060,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-02T05:44:21.815Z","etag":null,"topics":["binary-classification","data-analysis","data-preprocessing","data-visualization","feature-engineering","machine-learning","matplotlib","model-evaluation","nlp","pandas","predictive-modeling","python","scikit-learn","seaborn","supervised-learning"],"latest_commit_sha":null,"homepage":"","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/Zen204.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}},"created_at":"2024-08-17T20:48:47.000Z","updated_at":"2024-12-26T06:35:08.000Z","dependencies_parsed_at":"2024-11-03T04:00:37.510Z","dependency_job_id":"7da7f348-a1bb-467b-882b-93e731b0cd9b","html_url":"https://github.com/Zen204/airbnb-availability","commit_stats":{"total_commits":13,"total_committers":1,"mean_commits":13.0,"dds":0.0,"last_synced_commit":"9ebdfe5892a38ac6e64f231e3c83e84ed6736d50"},"previous_names":["zen204/ml_airbnb_availability","zen204/airbnb-availability"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Zen204%2Fairbnb-availability","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Zen204%2Fairbnb-availability/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Zen204%2Fairbnb-availability/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Zen204%2Fairbnb-availability/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Zen204","download_url":"https://codeload.github.com/Zen204/airbnb-availability/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247675631,"owners_count":20977376,"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","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":["binary-classification","data-analysis","data-preprocessing","data-visualization","feature-engineering","machine-learning","matplotlib","model-evaluation","nlp","pandas","predictive-modeling","python","scikit-learn","seaborn","supervised-learning"],"created_at":"2024-12-21T04:23:00.582Z","updated_at":"2026-01-21T01:02:02.041Z","avatar_url":"https://github.com/Zen204.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Predicting Airbnb Availability\n\nThis program is designed to predict whether an Airbnb listing is available using machine learning techniques. The project leverages feature engineering, data preprocessing, and supervised learning models to achieve accurate predictions.\n\n## Features\n\n- **Data Preprocessing:** Handles missing data, encodes categorical variables, and scales numerical features for optimal model performance.\n- **Feature Engineering:** Extracts relevant features to improve prediction accuracy.\n- **Modeling:** Trains and evaluates supervised learning models to predict Airbnb availability.\n- **Visualization:** Includes plots to analyze data trends and model performance.\n\n## Requirements\n\nTo run the notebook, you need the following dependencies:\n\n- Python 3.7+\n- Jupyter Notebook or JupyterLab\n- pandas\n- numpy\n- scikit-learn\n- matplotlib\n- seaborn\n\nInstall the required libraries using the following command:\n\n```bash\npip install -r requirements.txt\n```\n\n## Usage\n\n1. Clone the repository:\n\n   ```bash\n   git clone https://github.com/yourusername/airbnb-availability-predictor.git\n   ```\n\n2. Navigate to the project directory:\n\n   ```bash\n   cd airbnb-availability-predictor\n   ```\n\n3. Launch Jupyter Notebook:\n\n   ```bash\n   jupyter notebook Listings_Availability.ipynb\n   ```\n\n4. Run the cells in the notebook sequentially to:\n\n   - Load and preprocess the data\n   - Perform exploratory data analysis (EDA)\n   - Train and evaluate machine learning models\n\n## Dataset\n\nThe dataset includes Airbnb listings with various features such as location, price, and previous booking history. These attributes are used to predict the availability status of a listing.\n\n\u003e **Note:** Ensure you have the required dataset in the specified location before running the notebook. Replace the placeholder path in the notebook with your actual dataset path.\n\n## Results\n\nThe notebook provides:\n\n- A detailed analysis of features impacting availability.\n- Performance metrics (e.g., accuracy, precision, recall) of the trained models.\n- Visualizations to understand data distribution and model predictions.\n\n## Contributing\n\nContributions are welcome! If you have ideas for improving the project or adding new features, feel free to submit a pull request.\n\n## License\n\nThis project is licensed under the MIT License. See the `LICENSE` file for details.\n\n## Acknowledgments\n\nThank you to my mentors at MIT for all their support throughout this learning process!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzen204%2Fairbnb-availability","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzen204%2Fairbnb-availability","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzen204%2Fairbnb-availability/lists"}