mohamedkhayat/DIYNeuralNet
A lightweight deep learning framework implemented from scratch using NumPy/CuPy. supports customizable architectures, forward and back propagation, dropout, He/Glorot init, and mini-batch training. Designed for flexibility,it provides a foundation for building neural networks while giving insights into the inner workings of deep learning models
Stars
6
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 01, 2026
Commits (30d)
0
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