| # Neural Network Playground | |
| An interactive web-based application for visualizing and experimenting with neural network architectures. | |
| ## Features | |
| - **Drag-and-Drop Interface**: Easily create neural network architectures by dragging and dropping different layer types | |
| - **Multiple Layer Types**: Support for Input, Hidden, Output, Convolutional, and Pooling layers | |
| - **Dynamic Connections**: Create connections between layers to define your network topology | |
| - **Visual Styling**: Beautiful gradient-based styling for different layer types with animations | |
| - **Layer Properties**: View and edit detailed properties for each layer | |
| - **Network Validation**: Automatic validation of network architectures | |
| - **Training Simulation**: Visual simulation of the training process | |
| - **Responsive Design**: Works on desktop and mobile devices | |
| ## Getting Started | |
| 1. Clone this repository | |
| 2. Open `index.html` in your browser or use a local server: | |
| ``` | |
| python -m http.server | |
| ``` | |
| 3. Visit `http://localhost:8000` in your browser | |
| ## How to Use | |
| 1. Drag layer components from the left panel onto the canvas | |
| 2. Connect layers by dragging from output ports (right side) to input ports (left side) | |
| 3. Click on a layer to view its properties | |
| 4. Edit layer properties by clicking the edit button | |
| 5. Click "Run Network" to simulate training | |
| ## Technologies Used | |
| - HTML5 | |
| - CSS3 (with animations and gradients) | |
| - JavaScript (vanilla) | |
| - No external libraries required! | |
| ## License | |
| MIT | |
| ## Contributing | |
| Contributions, issues, and feature requests are welcome! |