Shypd.aiThe largest open index of AI toolsNeural-Network-Visualisation is an interactive web tool for visualizing a multi-layer perceptron trained on the MNIST handwritten digit dataset. Users can draw a digit and observe activations propagate through the network in 3D with real-time prediction probabilities.
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Neural-Network-Visualisation offers an interactive web-based visualization for a compact multi-layer perceptron, specifically trained on the MNIST handwritten digit dataset. Users can draw digits on a 28x28 grid and observe in real-time how activations propagate through the 3D network. The tool also displays prediction probabilities, providing a clear understanding of the neural network's decision-making process. It highlights the strongest incoming connections per neuron and uses color-coding to represent activation sign and magnitude. The project is open-source and provides Python helper scripts for training the MLP and exporting weights, supporting Apple Metal, CUDA, or CPU acceleration. It also includes a timeline export feature, allowing users to scrub through different training checkpoints.
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