{"id":20337957,"url":"https://github.com/uznetdev/competition-for-nt-4th-month","last_synced_at":"2026-05-22T16:33:16.964Z","repository":{"id":260620510,"uuid":"871213829","full_name":"UznetDev/Competition-for-NT-4th-month","owner":"UznetDev","description":null,"archived":false,"fork":false,"pushed_at":"2024-11-01T11:57:35.000Z","size":1717,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-04T14:32:52.114Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/UznetDev.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":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-11T13:49:05.000Z","updated_at":"2024-11-01T11:57:38.000Z","dependencies_parsed_at":"2024-11-01T12:28:43.179Z","dependency_job_id":"a96b7026-51e5-4d17-9528-fe3795a5dc82","html_url":"https://github.com/UznetDev/Competition-for-NT-4th-month","commit_stats":null,"previous_names":["uznetdev/competition-for-nt-4th-month"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/UznetDev/Competition-for-NT-4th-month","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UznetDev%2FCompetition-for-NT-4th-month","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UznetDev%2FCompetition-for-NT-4th-month/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UznetDev%2FCompetition-for-NT-4th-month/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UznetDev%2FCompetition-for-NT-4th-month/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/UznetDev","download_url":"https://codeload.github.com/UznetDev/Competition-for-NT-4th-month/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UznetDev%2FCompetition-for-NT-4th-month/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33354036,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-21T12:23:38.849Z","status":"online","status_checked_at":"2026-05-22T02:00:06.671Z","response_time":265,"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":"2024-11-14T21:11:01.077Z","updated_at":"2026-05-22T16:33:16.947Z","avatar_url":"https://github.com/UznetDev.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Competition for NT - 4th Month\n\nThis repository contains the notebook and resources for the **4th Month Competition for NT**. This competition involves analyzing a dataset, performing feature engineering, visualizations, and training a predictive model using various Python libraries.\n\n## Table of Contents\n- [Project Overview](#project-overview)\n- [Dataset](#dataset)\n- [Requirements](#requirements)\n- [Installation](#installation)\n- [Notebook Structure](#notebook-structure)\n- [Usage](#usage)\n- [Results](#results)\n- [Contributing](#contributing)\n- [License](#license)\n\n## Project Overview\nThe main objective of this competition is to analyze the given data, explore relationships between features, and develop a model to make predictions based on the processed dataset. The notebook explores feature correlations, visualizes data distributions, and builds a machine learning model to meet the competition's objectives.\n\n## Dataset\nDetails about the dataset and its contents:\n- **Data Loading**: The dataset is loaded and initially explored to understand the features and target variable.\n- **Preprocessing**: Includes handling missing values, scaling, and other transformations.\n\nNote: Ensure you have access to the dataset files as they may not be included in this repository.\n\n## Requirements\nThe primary libraries required for this project are:\n- `pandas`\n- `numpy`\n- `phik` (for advanced correlation analysis)\n- `scipy`\n- `matplotlib`\n- `seaborn`\n- `plotly`\n\nYou can install all requirements with:\n```bash\npip install pandas numpy phik scipy matplotlib seaborn plotly\n```\n\n## Installation\n1. Clone the repository:\n    ```bash\n    git clone https://github.com/UznetDev/Competition-for-NT-4th-month.git\n    cd Competition-for-NT-4th-month\n    ```\n\n2. Install the dependencies listed above.\n    ```sh\n    pip install -r requirements.txt\n    ```\n\n## Notebook Structure\nThe notebook follows a structured workflow, outlined as follows:\n\n1. **Setup and Imports**: Imports necessary libraries and sets up the environment.\n2. **Data Loading**: Loads the dataset, explores the structure, and checks for missing values.\n3. **Feature Engineering and Correlation Analysis**: Uses `phik` and other correlation measures to identify important features.\n4. **Visualizations**: Visualizes feature distributions and correlations.\n5. **Model Training**: Trains a predictive model and evaluates its performance on the dataset.\n6. **Evaluation**: Evaluates the model's performance metrics to gauge its effectiveness in solving the competition's problem.\n\n## Usage\n1. Open the notebook `Competition_for_NT_4th_month.ipynb` in Jupyter or Google Colab.\n2. Run each cell step-by-step to reproduce the analysis and model training.\n3. Modify parameters and experiment with different models to improve performance.\n\n### Running in Google Colab\nTo run the notebook in Google Colab, open the following link:\n[Open in Colab](https://colab.research.google.com/github/UznetDev/Competition-for-NT-4th-month/blob/main/Competition_for_NT_4th_month.ipynb)\n\n## Results\nThe notebook details the final results, including the accuracy or other performance metrics. Visualizations of the data and feature correlations are provided to illustrate key insights.\n\n## Contributing\nContributions are welcome! Please open an issue to discuss potential changes or improvements.\n\n## License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuznetdev%2Fcompetition-for-nt-4th-month","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuznetdev%2Fcompetition-for-nt-4th-month","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuznetdev%2Fcompetition-for-nt-4th-month/lists"}