https://github.com/vansh-py04/convolution-net-from-scratch
A minimal NumPy-based implementation of a 3-layer convolutional neural network (CNN) from scratch — including custom forward and backward passes for conv, ReLU, pooling, affine, and softmax layers. Perfect for learning how CNNs actually work under the hood.
https://github.com/vansh-py04/convolution-net-from-scratch
backpropagation cnn computer-vision convolutional-neural-networks cs231n cs231n-assignment deep-learning from-scratch from-scratch-in-python fully-connected-network machine-learning maxpool2d nueral-networks numpy softmax stanford-deep-learning
Last synced: 4 months ago
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A minimal NumPy-based implementation of a 3-layer convolutional neural network (CNN) from scratch — including custom forward and backward passes for conv, ReLU, pooling, affine, and softmax layers. Perfect for learning how CNNs actually work under the hood.
- Host: GitHub
- URL: https://github.com/vansh-py04/convolution-net-from-scratch
- Owner: vansh-py04
- Created: 2025-05-10T12:09:26.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-05-20T05:38:12.000Z (5 months ago)
- Last Synced: 2025-05-20T09:11:39.427Z (5 months ago)
- Topics: backpropagation, cnn, computer-vision, convolutional-neural-networks, cs231n, cs231n-assignment, deep-learning, from-scratch, from-scratch-in-python, fully-connected-network, machine-learning, maxpool2d, nueral-networks, numpy, softmax, stanford-deep-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 271 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md