RAHAMNIabdelkaderseifelislem/NeuroForge

🧠 NeuroForge is an intuitive drag-and-drop tool for building and training neural networks, featuring data preprocessing, interactive visualizations, and automated model architecture design. Built with PyTorch and Streamlit, it simplifies the deep learning workflow from data preparation to model deployment with GPU acceleration support.

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Experimental

NeuroForge helps researchers, analysts, and students quickly build and train neural networks without needing to write code. You upload your CSV or Excel data, which is then preprocessed and visualized, and you can then drag and drop layers to design and train your neural network, getting a trained model in return. It's designed for anyone looking to experiment with deep learning models, especially those new to coding or who prefer a visual interface.

No commits in the last 6 months.

Use this if you need to quickly prototype or train simple neural networks from tabular data using a visual, drag-and-drop interface, especially if you want to leverage GPU acceleration.

Not ideal if you require advanced custom neural network layers, sophisticated data preprocessing transformations, or highly complex model architectures not covered by basic linear or convolutional layers.

deep-learning-prototyping machine-learning-education data-science-experimentation neural-network-design visual-modeling
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 0 / 25

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Language

Python

License

Last pushed

Nov 18, 2024

Commits (30d)

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