An Elegant Neural Network User Interface to build drag-and-drop neural networks, train in the browser, visualize during training, and export to Python.
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ENNUI is an Elegant Neural Network User Interface that allows users to:

  • Build neural network architectures with a drag and drop interface.
  • Train those networks on the browser.
  • Visualize the training process.
  • Export to Python.

Thanks to Gil Strang, it's hosted at https://math.mit.edu/ENNUI/


After cloning the repo, to install dependencies, run: npm install

To Build the app, run: npm run build

For Continuous Build and Integration, run: npm run watch

To use chrome with localhost and the CIFAR-10 Dataset, make sure to close all chrome windows and run the following command to launch chrome: 'path/to/chrome.exe --allow-file-access-from-files'

Code Structure

ENNUI is frontend-only. The implementation is structed in two parts:

  • ENNUI/src/ui is home to the traditional frontend components such as the styling, the button logic, and the draggable components (e.g. the layers and activations).
  • ENNUI/src/model is the "backend" implementation supporting core functionality such as building neural networks, doing the code generation, and saving the state in the browser.
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