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https://github.com/aaaastark/perceptron-neural-network
Artificial Natural Network Perceptron (Forward Pass and Back Propagation). Weights and Bias. Forward Pass: Net Input Function, Activation Function (Sigmoid). Threshold. Back Propagation: Binary Cross Entropy Loss, Computing Gradients/ Slopes/ Derivatives, Gradient Descent Step, Epoch.
https://github.com/aaaastark/perceptron-neural-network
artificial-neural-networks bias epoch gradient-descent perceptron python sigmoid threshold
Last synced: about 2 months ago
JSON representation
Artificial Natural Network Perceptron (Forward Pass and Back Propagation). Weights and Bias. Forward Pass: Net Input Function, Activation Function (Sigmoid). Threshold. Back Propagation: Binary Cross Entropy Loss, Computing Gradients/ Slopes/ Derivatives, Gradient Descent Step, Epoch.
- Host: GitHub
- URL: https://github.com/aaaastark/perceptron-neural-network
- Owner: aaaastark
- Created: 2022-05-11T21:36:47.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-05-11T21:45:39.000Z (over 2 years ago)
- Last Synced: 2023-07-08T15:34:15.453Z (over 1 year ago)
- Topics: artificial-neural-networks, bias, epoch, gradient-descent, perceptron, python, sigmoid, threshold
- Language: Jupyter Notebook
- Homepage: https://github.com/aaaastark/perceptron-neural-network
- Size: 60.5 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0