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Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
🍊 Intro to symbolic computation in Python including applications to function optimization, physics simulation and more. Includes notebooks on back-propagation, auto-diff and more.
Golang implementation of a single hidden layer feed forward neural network based on the Python notebook for Make Your Own Neural Network by Tariq Rashid
This repository contains Python notebook which contains creation of simple neural network. I have used synthesised 2 cluster dataset to train the network and test it.
Backpropagation is a standard method for training a Neural Network. With this notebook, my attempt is to explain how it works with an explicit example.