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nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is great for customization and teaching purposes.
Features
- Real-time visualization of neural network inference
- Displays input, hidden, and output layers with connections
- Uses OpenGL and Pygame for smooth rendering
- Interactive UI with user-controlled input
- Weight and activation values visualized through color and size
- Adjustable network parameters for experimentation
- Minimalist code for educational customization
- Step-by-step propagation display
- Supports feedforward neural networks
Project Samples
Categories
Neural Network LibrariesLicense
MIT LicenseFollow Neural Network Visualization
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