A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN

一文彻底搞懂BP算法：原理推导+数据演示+项目实战

A tiny neural network 🧠

Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

matrix square root and its gradient

Back Propagation, Python

Фреймворк для построения нейронных сетей, комитетов, создания агентов с параллельными вычислениями.

Efficiently performs automatic differentiation on arbitrary functions. Basically a rudimentary version of Tensorflow.

MATLAB implementations of a variety of machine learning/signal processing algorithms.

Neural Network in pure PHP

Minimalist deep learning library with first and second-order optimization algorithms made for educational purpose

Neural network/Back Propagation implemented from scratch for MNIST.从零开始实现神经网络和反向传播算法，识别MNIST

Training an artificial neural network using back-propagation on MNIST dataset

Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

MNIST Classification using Neural Network and Back Propagation. Written in Python and depends only on Numpy

Multi-layered Convolutional Neural Network written in C++11

A basic implementation of a neural network in java, with back-propagation. Created for learning purposes.

Implementation of the back-propagation algorithm using only the linear algebra and other mathematics tool available in numpy and scipy.

BSc Thesis at FER-2019/20 led by doc. dr. sc. Marko Čupić