Multivariate Regression and Classification Using a Feed-Forward Neural Network and Gradient Descent Optimization.

🤖 Artificial intelligence (neural network) proof of concept to solve the classic XOR problem. It uses known concepts to solve problems in neural networks, such as Gradient Descent, Feed Forward and Back Propagation.

Neural Net using Backpropagation with momentum.

Implementation of some simple Neural-Networks for binary classification with newff toolbox in Matlab

Coursework on Neural Networks for the Μ124 - Machine Learning course, NKUA, Fall 2022.

Simple Feedforward Neural Network with Backpropagation Algorithm

[RU] Обучение многослойного перцептрона с одним скрытым слоем методом обратного распространения ошибки. [EN] Training of a multilayer perceptron with one hidden layer by the back-propagating errors method.

The main goal of this project is to implement the well-known backpropagation algorithm in an easy manner based on the idea of the F-adjoint propagation.

Implementing the backpropagation algorithm for Neural Networks

A backpropagation algorithm is implemented in Python from scratch to perform a classification analysis.

backpropagation algorithm with one hidden layer using MNIST Handwriting Digits

A machine learning library written in C. From scratch, zero dependencies (except for the C standard library).

Neural backpropagation with examples and training (Java)

Implementation of Back Propagation algorithm along with its variants such as RProp and QuickProp.

I made a Multi Layer Perceptron(Neural Network) in numpy

it is simple 2 layer neural network using only numpy as dependency

反向传播算法的简单实现，对照了tf的api

Python implementation of the backpropagation algorithm.

Using only numpy in Python, a neural network with a forward and backward method is used to classify given points (x1, x2) to a color of red or blue.