This repository contains the implementation of an Approximate Nearest Neighbor Search (ANNS) algorithm on the Fashion-MNIST dataset using Python.
📖 Dataset The Fashion-MNIST dataset is a collection of 60,000 labeled images of 10 different fashion categories. Each image is a 28x28 grayscale image, and the dataset is split into a training set of 50,000 images and a test set of 10,000 images.
🚀 Getting Started To get started with this project, follow these steps:
Download it from Kaggle: https://www.kaggle.com/datasets/zalando-research/fashionmnist Install the required dependencies: pip install -r requirements.txt Download the Fashion-MNIST dataset and place it in the data directory.
🤝 Contributing Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request.
📜 License This project is licensed under the MIT License.
Feel free to use this code for educational and personal projects.
📧 Contact If you have any questions or need further assistance, feel free to contact the project maintainer at [email protected].
Happy coding! 👩💻👨💻