{"id":22912585,"url":"https://github.com/niklashenning/handwritten-digit-recognition","last_synced_at":"2026-03-09T10:01:17.119Z","repository":{"id":265564479,"uuid":"860675258","full_name":"niklashenning/handwritten-digit-recognition","owner":"niklashenning","description":"Handwritten digit recognition machine learning model (HwD-1000 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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":["classification","computer-vision","digit-recognition","handwriting-recognition","image-classification","machine-learning"],"created_at":"2024-12-14T04:29:17.117Z","updated_at":"2026-03-09T10:01:17.102Z","avatar_url":"https://github.com/niklashenning.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eHandwritten Digit Recognition\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n    A machine learning model that recognizes handwritten digits based on my\n    \u003ca href=\"https://github.com/niklashenning/hwd-1000-dataset\"\u003eHwD-1000 dataset\u003c/a\u003e.\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003cimg src=\"https://github.com/user-attachments/assets/3ca61c98-4403-4f69-b34e-17dbe8139fc3\" width=\"250\"\u003e\n\u003c/p\u003e\n\n\n## About\nThis basic machine learning model is trained on the [HwD-1000 dataset](https://github.com/niklashenning/hwd-1000-dataset)\nand is able to accurately classify and recognize digits from images.\u003cbr\u003e\nIt utilizes PyTorch's neural networks and Tensor libraries for training the model, pandas for loading\nand handling the dataset, Pillow for loading and converting the images, and Matplotlib\nfor visualizing the training results.\n\n\n## Dataset\nThe dataset contains 1000 images of single digits (0-9) that have been manually drawn on a white\n28x28 px background with a black pen in varying widths and styles.\n\n\u003cimg src=\"https://github.com/user-attachments/assets/6b84dd91-b959-472a-a3b6-e327c1826a3d\"\u003e\n\n\n## Results\nThe neural network was trained for 50 epochs with a learning rate of 0.001 using AdamW\nas the optimizer and CrossEntropyLoss as the criterion. Training was done on 80%\nof the dataset while the remaining 20% were used to validate the results.\n\nThe model achieved an accuracy of 99.50% on the validation data.\n\n```\nTest Accuracy: 99.50% (199/200)\n```\n\n| Epoch | Loss     |\n|-------|----------|\n| 1     | 1.506903 |\n| 10    | 0.047416 |\n| 20    | 0.011299 |\n| 30    | 0.006869 |\n| 40    | 0.002777 |\n| 50    | 0.001392 |\n\n\u003cimg src=\"https://github.com/user-attachments/assets/70aec14d-2f0c-4b1f-a39c-050bc1db0cbb\" width=\"500\"\u003e\n\n\n## License\nThis software is licensed under the [MIT license](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fniklashenning%2Fhandwritten-digit-recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fniklashenning%2Fhandwritten-digit-recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fniklashenning%2Fhandwritten-digit-recognition/lists"}