ML Dataset Explorer is a modern, minimalist UI platform designed for learners and practitioners to experiment with prefilled datasets and understand how they impact machine learning model performance. The platform provides an interactive environment where users can compare different ML models (e.g., classification, regression) using dynamic visualizations, making it easy to grasp which datasets yield the best results and why.
You can experience ML Dataset Explorer directly via this deployment:
https://ml-dataset-explorer.vercel.app/
ML Dataset Explorer serves as an educational tool that bridges the gap between theoretical machine learning concepts and real-world data experimentation. By allowing users to interact with a curated selection of prefilled datasets and compare performance metrics across various ML models, the platform simplifies complex topics and highlights the relationship between dataset characteristics and model effectiveness.
- Interactive Visualizations: Dynamic charts, graphs, and tables update based on user selections to show key performance metrics such as accuracy, precision, and speed.
- Dataset Exploration: Easily browse and select from multiple prefilled datasets using intuitive dropdown menus and filter options.
- Model Comparison: Toggle between different machine learning models to see comparative performance insights.
- Learning Resources: Access integrated tutorials, guides, and contextual explanations that demystify why certain models work better with specific types of data.
- Responsive Design: Enjoy a consistent user experience across desktops, tablets, and mobile devices.
- Clean & Minimalist UI: Focus on clarity and ease of use with a modern design that encourages interactive learning.
- Clone the Repository:
git clone https://github.com/yourusername/ml-dataset-explorer.git cd ml-dataset-explorer - Install Dependencies:
npm install
- Start the Development Server:
npm start
- Visit the Platform: Open your browser and navigate to http://localhost:3000 to see the platform in action.
- Navigation: Use the sidebar or navigation bar to switch between the Data Exploration, Model Comparison, and Learning Resources sections.
- Dataset Selection: Choose from various prefilled datasets using the dropdown menus. The central display area will update with interactive visualizations based on your selection.
- Model Toggling: Easily switch between different ML models to compare performance metrics. Visual components like charts and graphs will update in real time.
- Learning: Refer to the dedicated Learning Resources section for guides and contextual explanations that clarify how dataset characteristics affect model performance.
This section is designed to help you deepen your understanding of machine learning:
- Guides & Tutorials: Step-by-step instructions on how to interpret various performance metrics.
- Best Practices: Insights into selecting the right datasets and optimizing models.
- Case Studies: Examples demonstrating the relationship between dataset characteristics and model effectiveness.
- Further Reading: Links to external resources and research papers for additional learning.
We welcome contributions to improve ML Dataset Explorer! To contribute:
- Fork the repository.
- Create a new branch for your feature or bug fix:
git checkout -b feature/my-new-feature
- Commit your changes:
git commit -am 'Add new feature' - Push to your branch:
git push origin feature/my-new-feature
- Open a pull request detailing your changes.
For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or feedback, please reach out:
- Maintainer: Naitik Shah
- Email: [email protected]
- GitHub: naitik2314