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https://github.com/vtramo/neural-networks-experiments-from-scratch
The objective of this repository is to provide a learning and experimentation environment to better understand the details and fundamental concepts of neural networks by building neural networks from scratch.
https://github.com/vtramo/neural-networks-experiments-from-scratch
activation-functions backpropagation batch-learning classification-problem early-stopping gradient-based-algorithm improved-resilient-backpropagation irprop kfold-cross-validation minibatch momentum neural-network numpy online-learning python python3 resilient-backpropagation rprop softmax stochastic-gradient-descent
Last synced: 1 day ago
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The objective of this repository is to provide a learning and experimentation environment to better understand the details and fundamental concepts of neural networks by building neural networks from scratch.
- Host: GitHub
- URL: https://github.com/vtramo/neural-networks-experiments-from-scratch
- Owner: vtramo
- Created: 2023-06-08T19:13:27.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-07-22T08:39:26.000Z (over 1 year ago)
- Last Synced: 2023-09-02T15:12:00.377Z (about 1 year ago)
- Topics: activation-functions, backpropagation, batch-learning, classification-problem, early-stopping, gradient-based-algorithm, improved-resilient-backpropagation, irprop, kfold-cross-validation, minibatch, momentum, neural-network, numpy, online-learning, python, python3, resilient-backpropagation, rprop, softmax, stochastic-gradient-descent
- Language: Python
- Homepage:
- Size: 12.2 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0