# Neural Network

## Simple Neural Network

* [Neural Network From Scratch](https://sirupsen.com/napkin/neural-net)
* [eriklindernoren/ML-From-Scratch: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.](https://github.com/eriklindernoren/ML-From-Scratch)
* [karpathy/micrograd: A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API](https://github.com/karpathy/micrograd)
* [parasdahal/deepnet: Implementation of CNNs, RNNs, and many deep learning techniques in plain Numpy.](https://github.com/parasdahal/deepnet)
* [Yet another backpropagation tutorial–Windows On Theory](https://windowsontheory.org/2020/11/03/yet-another-backpropagation-tutorial/)
* [Neural Networks from Scratch](https://nnfs.io/)
* [Neural Networks from Scratch - P.1 Intro and Neuron Code - YouTube](https://www.youtube.com/watch?v=Wo5dMEP_BbI)
* [Make a Neural Network in Excel, AI for Business People](https://www.linkedin.com/pulse/make-neural-network-excel-ai-business-people-aaron-butler)
* [Demystifying Feed-forward and Back-propagation using MS Excel - by Gaurav Gupta - Towards Data Science](https://towardsdatascience.com/demystifying-feed-forward-and-back-propagation-using-ms-excel-30f5aeefcfc7)
* [AngelNikoloff/Neural-Network-in-spreadsheet: Simple Artificial Neural Network with Backpropagation in Excel spreadsheet with XOR example - for education purpose;](https://github.com/AngelNikoloff/Neural-Network-in-spreadsheet)
* [Neural Networks Learning The Basics: Backpropagation–Samzee\_Codes](https://samzee.net/2019/02/20/neural-networks-learning-the-basics-backpropagation/)
* [Machine Learning in Excel - CodeProject](https://www.codeproject.com/Articles/1273000/Machine-Learning-in-Excel)
* [3Blue1Brown](https://www.3blue1brown.com/topics/neural-networks)
* [module0—MiniTorch 0.1 documentation](https://minitorch.github.io/)

## Neural Network with Resistor

* [Demonstration of Decentralized, Physics-Driven Learning](https://arxiv.org/abs/2108.00275)
* [Learning Without a Global Clock: Asynchronous Learning in a Physics-Driven Learning Network](https://arxiv.org/abs/2201.04626)
* [Simple electrical circuit learns on its own—with no help from a computer - Science - AAAS](https://www.science.org/content/article/simple-electrical-circuit-learns-its-own-no-help-computer)

## Neural Network

* [A Neural Network Playground](https://playground.tensorflow.org/#activation=tanh\&batchSize=10\&dataset=circle\&regDataset=reg-plane\&learningRate=0.03\&regularizationRate=0\&noise=0\&networkShape=4,2\&seed=0.94939\&showTestData=false\&discretize=false\&percTrainData=50\&x=true\&y=true\&xTimesY=false\&xSquared=false\&ySquared=false\&cosX=false\&sinX=false\&cosY=false\&sinY=false\&collectStats=false\&problem=classification\&initZero=false\&hideText=false)

## Neural Network

* [Neural Networks from Scratch](https://aegeorge42.github.io/)
* [Neural Networks from Scratch](https://nnfs.io/)
* [Neural Networks, Manifolds, and Topology -- colah's blog](https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/)

## Physical Neural Network

* [Deep physical neural networks trained with backpropagation - Nature](https://www.nature.com/articles/s41586-021-04223-6)
