https://github.com/yasinshafiei/fullyconnected-from-scratch
Fully connected layer from scratch, with training on MNIST dataset
https://github.com/yasinshafiei/fullyconnected-from-scratch
adam-optimizer ai ann artificial artificial-intelligence deep-learning from-scratch mlp neural-network numpy perceptron python
Last synced: about 2 months ago
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Fully connected layer from scratch, with training on MNIST dataset
- Host: GitHub
- URL: https://github.com/yasinshafiei/fullyconnected-from-scratch
- Owner: YasinShafiei
- Created: 2024-01-16T20:36:24.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-18T12:46:10.000Z (about 2 years ago)
- Last Synced: 2025-02-27T02:24:38.906Z (over 1 year ago)
- Topics: adam-optimizer, ai, ann, artificial, artificial-intelligence, deep-learning, from-scratch, mlp, neural-network, numpy, perceptron, python
- Language: Python
- Homepage:
- Size: 12.7 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# FullyConnected neural network layer from scratch
Fully connected layer from scratch, with training on MNIST dataset.
The scripts are all for creating a Fully-Connected Neural Network layer and making a custom model.
Also the model trains on fully custom training loop. All the optimizer and loss function are written from scratch.
## Results
I implemented a MLP from scratch only using NumPy for model creation. Here are the results of the training:
## Article:
Please go and checkout my article about this project for full explanations and detils:
https://medium.com/@YasinShafiei/making-a-neural-network-fully-connected-layer-from-scratch-only-numpy-49bd7958b6f3