{"id":21559652,"url":"https://github.com/rvats20/digit-recognizer","last_synced_at":"2026-04-13T23:33:14.967Z","repository":{"id":263164015,"uuid":"889554330","full_name":"rvats20/Digit-Recognizer","owner":"rvats20","description":"This competition is the perfect introduction to techniques like neural networks using a classic dataset including pre-extracted features.","archived":false,"fork":false,"pushed_at":"2024-12-14T11:15:52.000Z","size":950,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-27T18:43:04.201Z","etag":null,"topics":["computer-vision","digit-recognition","kaggle","kaggle-competition","machine-learning-algorithms","python-3"],"latest_commit_sha":null,"homepage":"https://rvats20.github.io/portfolio/","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/rvats20.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":"2024-11-16T16:15:33.000Z","updated_at":"2024-12-14T11:15:55.000Z","dependencies_parsed_at":"2024-12-12T15:27:09.853Z","dependency_job_id":"37be5211-bd13-4bbb-8c8e-67aaca7e8f51","html_url":"https://github.com/rvats20/Digit-Recognizer","commit_stats":null,"previous_names":["rvats20/digit-recognizer"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rvats20%2FDigit-Recognizer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rvats20%2FDigit-Recognizer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rvats20%2FDigit-Recognizer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rvats20%2FDigit-Recognizer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rvats20","download_url":"https://codeload.github.com/rvats20/Digit-Recognizer/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244155520,"owners_count":20407363,"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":["computer-vision","digit-recognition","kaggle","kaggle-competition","machine-learning-algorithms","python-3"],"created_at":"2024-11-24T09:08:11.996Z","updated_at":"2026-04-13T23:33:14.923Z","avatar_url":"https://github.com/rvats20.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Digit Recognizer\n\nWelcome to the **Digit Recognizer** repository! This project is part of a Kaggle competition aimed at developing models to recognize handwritten digits from the famous MNIST dataset.\n\n## Table of Contents\n\n- Introduction\n- Competition Overview\n- Project Structure\n- Installation\n- Usage\n- Results\n- Contributing\n- License\n- Contact\n\n## Introduction\n\nHandwritten digit recognition is a classic problem in the field of computer vision and machine learning. This repository contains the code and resources used to participate in the Kaggle Digit Recognizer competition, where the goal is to correctly identify digits (0-9) from a dataset of handwritten images.\n\n## Competition Overview\n\n- **Host**: Kaggle\n- **Objective**: Build a model to accurately recognize handwritten digits.\n- **Dataset**: MNIST dataset, consisting of 60,000 training images and 10,000 test images.\n- **Evaluation Metric**: Accuracy of the model on the test set.\n\n\n## Installation\n\nTo get started with this project, clone the repository and install the required dependencies:\n\n```bash\ngit clone https://github.com/yourusername/Digit-Recognizer.git\ncd Digit-Recognizer\npip install -r requirements.txt\n```\n\n## Usage\n\n1. **Data Preprocessing**: Prepare the dataset for training and evaluation.\n   ```bash\n   python src/data_preprocessing.py\n   ```\n\n2. **Train the Model**: Train the digit recognition model on the prepared dataset.\n   ```bash\n   python src/model_training.py\n   ```\n\n3. **Evaluate the Model**: Assess the performance of the trained model.\n   ```bash\n   python src/model_evaluation.py\n   ```\n\n## Results\n\nOur model achieved an impressive accuracy of **XX.XX%** on the test set, demonstrating its effectiveness in recognizing handwritten digits. Detailed results and analysis can be found in the `Model_Evaluation.ipynb` notebook.\n\n## Contributing\n\nWe welcome contributions from the community! If you have any suggestions or improvements, please feel free to submit a pull request or open an issue.\n\n## License\n\nThis project is licensed under the MIT License. See the LICENSE file for more details.\n\n## Contact\n\nFor any questions or inquiries, please contact yourname.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frvats20%2Fdigit-recognizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frvats20%2Fdigit-recognizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frvats20%2Fdigit-recognizer/lists"}