https://github.com/johnmachado11/neural-networks-from-scratch-in-python
Building neural networks from scratch in pure Python (no 3rd party libraries), gradually incorporating NumPy for better math operations. This covers coding neurons, layering them, using activation functions, calculating loss, backpropagation, and optimizing parameters.
https://github.com/johnmachado11/neural-networks-from-scratch-in-python
Last synced: 6 months ago
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Building neural networks from scratch in pure Python (no 3rd party libraries), gradually incorporating NumPy for better math operations. This covers coding neurons, layering them, using activation functions, calculating loss, backpropagation, and optimizing parameters.
- Host: GitHub
- URL: https://github.com/johnmachado11/neural-networks-from-scratch-in-python
- Owner: JohnMachado11
- Created: 2024-06-15T23:29:18.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-12T13:01:42.000Z (7 months ago)
- Last Synced: 2025-03-12T14:19:49.763Z (7 months ago)
- Language: Python
- Homepage: https://nnfs.io/
- Size: 22 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Neural-Networks-from-Scratch-in-Python
https://nnfs.io/
https://nnfs.io/neural_network_animations
"Neural Networks From Scratch is a book intended to teach you how to build neural networks on your own, without any libraries, so you can better understand deep learning and how all of the elements work. This is so you can go out and do new/novel things with deep learning as well as to become more successful with even more basic models."
By Harrison Kinsley & Daniel Kukiela
Book Repo: https://github.com/Sentdex/nnfs_book