A dynamic multilayer neural network implementation with RProp for MNIST classification.
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Updated
Nov 5, 2023 - Python
A dynamic multilayer neural network implementation with RProp for MNIST classification.
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.
Autodiff is a numerical library for the Go programming language that supports automatic differentiation. It implements routines for linear algebra (vector/matrix operations), numerical optimization and statistics
RPROP Neural Network with Delphi
A simple FCNN and multitheading rProp implementation from scratch in C++.
Pure Golang implementation of the algorithm Rprop+
gradient descent optimization algorithms
Bachelor Thesis - Reinforcement learning using NFQ on humanoid robot NAO
A C++ implementation of feed-forward neural networks.
This doesn't work, not the code, the whole premise. Don't expect to get rich quick! The code behind this is a basic Feed Forward neural network, trained with RPROP, which I wrote from scratch. It doesn't have multithreading either, so not useful for most things.
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