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\n\n# 🚀 Introduction\n\nWelcome to the repository containing innovative software developed by Ultralytics 🧠. Our code is 🌟 **open-sourced and freely available for redistribution under the AGPL-3.0 license**. For more insight into our work and impact, head over to https://www.ultralytics.com.\n\n[![Ultralytics Actions](https://github.com/ultralytics/mnist/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/mnist/actions/workflows/format.yml)\n\n# 📗 Description\n\nThe repository at https://github.com/ultralytics/mnist is our dedicated playground for the MNIST dataset. 🖐 This repository houses sandbox code that allows for experimentation and training of different neural network architectures on the famous MNIST digit database.\n\n# 📦 Requirements\n\nEnsure you have Python 3.7 or later installed on your machine. The following packages are required, and you can install them using pip with the provided command: `pip3 install -U -r requirements.txt`.\n\n- `numpy`: A fundamental package for scientific computing in Python.\n- `torch`: PyTorch, an open-source machine learning library for Python.\n- `torchvision`: A PyTorch package that includes datasets and model architectures for computer vision.\n- `opencv-python`: An open-source computer vision and machine learning software library.\n\n# 🏃‍♂️ Run\n\nTo start training on the MNIST digits dataset, execute `train.py` from your Python environment. The training and test data are located in the `data/` folder and were initially curated by Yann LeCun (http://yann.lecun.com/exdb/mnist/).\n\n```python\n# Example snippet of train.py to showcase its usage.\n# This will set up the environment for training a model on MNIST dataset.\n\n# Import necessary libraries (Make sure they are installed as per requirements)\nimport torch\n\n# Your training script will start here, initialize models, load data, etc.\n# ...\n\n# Start the training process\n# ...\n\n# Save your trained model\ntorch.save(model.state_dict(), 'path_to_save_model.pt')\n\n# Add suitable comments to each segment of your code for better understanding.\n```\n\n![MNIST Examples](https://upload.wikimedia.org/wikipedia/commons/2/27/MnistExamples.png \"MNIST digits example\")\\\n_Image credit: [Josef Steppan](//commons.wikimedia.org/w/index.php?title=User:Jost_swd15&action=edit&redlink=1 \"User:Jost swd15 (page does not exist)\") - [Own work](//commons.wikimedia.org/wiki/File:MnistExamples.png), [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0 \"Creative Commons Attribution-Share Alike 4.0\"), [Link](https://commons.wikimedia.org/w/index.php?curid=64810040)_\n\n# 🤝 Contribute\n\nWe welcome contributions from the community! Whether you're fixing bugs, adding new features, or improving documentation, your input is invaluable. Take a look at our [Contributing Guide](https://docs.ultralytics.com/help/contributing) to get started. Also, we'd love to hear about your experience with Ultralytics products. Please consider filling out our [Survey](https://ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey). A huge 🙏 and thank you to all of our contributors!\n\n\n\n\n $\"Ultralytics$ \n\n# ©️ License\n\nUltralytics is excited to offer two different licensing options to meet your needs:\n\n- **AGPL-3.0 License**: Perfect for students and hobbyists, this [OSI-approved](https://opensource.org/licenses/) open-source license encourages collaborative learning and knowledge sharing. Please refer to the [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for detailed terms.\n- **Enterprise License**: Ideal for commercial use, this license allows for the integration of Ultralytics software and AI models into commercial products without the open-source requirements of AGPL-3.0. For use cases that involve commercial applications, please contact us via [Ultralytics Licensing](https://ultralytics.com/license).\n\n# 📬 Contact Us\n\nFor bug reports, feature requests, and contributions, head to [GitHub Issues](https://github.com/ultralytics/mnist/issues). For questions and discussions about this project and other Ultralytics endeavors, join us on [Discord](https://ultralytics.com/discord)!\n\n
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\n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n $\"space\"$ \n $\"Ultralytics$ \n

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ultralytics/mnist

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