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Search results for network backpropagation
backpropagation
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network
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76 search results found
Genann
⭐
1,398
simple neural network library in ANSI C
Neataptic
⭐
978
🚀 Blazing fast neuro-evolution & backpropagation for the browser and Node.js
Simple Neural Network
⭐
723
A simple Python script showing how the backpropagation algorithm works.
Factor Network
⭐
525
A simple factor network implementation written by JavaScript
Go Deep
⭐
436
Artificial Neural Network
Gonn
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334
GoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN
Python Neural Network
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278
This is an efficient implementation of a fully connected neural network in NumPy. The network can be trained by a variety of learning algorithms: backpropagation, resilient backpropagation and scaled conjugate gradient learning. The network has been developed with PYPY in mind.
Deepneuralclassifier
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243
Deep neural network using rectified linear units to classify hand written symbols from the MNIST dataset.
Neural Network From Scratch
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211
Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?
Make_a_neural_network
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196
This is the code for the "Make a Neural Network" - Intro to Deep Learning #2 by Siraj Raval on Youtube
Deeplearning Notes
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194
Notes for Deep Learning Specialization Courses led by Andrew Ng.
Probabilistic Backpropagation
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159
Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
Nn
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117
A tiny neural network 🧠
Neural Net Ruby
⭐
105
A neural network, written in Ruby
Deep Learning Coursera
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102
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
Sentiment
⭐
85
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
Neuroduino
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79
An artificial neural network library for the Arduino
Minimal Nn
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73
A minimal implementation of neural network for MNIST experiment. Used as an exercise to help understanding Backpropagation by implementing it in NumPy.
Theoretical Proof Of Neural Network Model And Implementation Based On Numpy
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66
This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。
Bnns Cocoa Example
⭐
59
An example of a neural network trained by tensorflow and executed using BNNS
Ann.jl
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58
Julia artificial neural networks
Neuralduino
⭐
35
The only dynamic and reconfigurable Artificial Neural networks library with back-propagation for arduino
Biopy
⭐
29
Biologically-Inspired and Machine Learning Algorithms written in Python
Swiftsimpleneuralnetwork
⭐
28
A simple multi-layer feed-forward neural network with backpropagation built in Swift.
Tssl Bp
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26
Pytorch implementation of TSSL-BP rule for Deep Spiking Neural Networks.
Hfnn
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25
Dl Glossary
⭐
25
📑 The Open Source Deep Learning Glossary
Cerebrum
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24
Cerebrum.js is a neural network library created in pure JavaScript.
Gabornet
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24
Newbie_neural_network_practice
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21
适合新手学习的神经网络实践教程+代码。a awesome neural network practice project for newbie.我的CSDN博客:
Minimalistic Multiple Layer Neural Network From Scratch In Python
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21
Minimalistic Multiple Layer Neural Network from Scratch in Python.
Bohp_rnn
⭐
20
Backprop training of recurrent neural networks with Hebbian plastic connections
Littlebrain
⭐
17
Multi-layer Neural Network in Javascript
Backpropagation
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17
Neural Network Backpropagation Algorithm. Implementation using python
Ai Backpropagation
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15
The backpropagation algorithm explained and demonstrated.
Recurrent Js
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14
[INACTIVE] Amazingly simple to build and train various neural networks. The library is an object-oriented neural network approach (baked with Typescript), containing stateless and stateful neural network architectures.
Neural Network With Genetic Algorithm Optimizer
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13
Train neural network with genetic algorithm (alternative method to backpropagation)
Neural Networks Py
⭐
12
Core neural networks framework supporting to build multilayer perceptron
Quantum Backpropagation
⭐
12
Simple demo showcasing baseline logic for BaQProp to learn "quantum data" [outdated]
Jnn
⭐
12
Backpropagation neural-network API for Java
Backpropagation C
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12
Available when training a Neural Network, or an Autoencoder.
Neuralnetwork
⭐
11
numpy implementation of a feed forward neural network with backpropagation
Neuralnetwork
⭐
11
This java library is used for generating, training, and using artificial neural networks with linear algebra. Uses feed forward nets, with backpropagation learning algorithm.
Genetic Neural Network
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11
Training a Neural Network using Genetic Algorithm.
Neural Network In Spreadsheet
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11
Simple Artificial Neural Network with Backpropagation in Excel spreadsheet with XOR example - for education purpose;
Brainth
⭐
10
A deep, functional, idiomatic, neural-network in Clojure.
Nim Rmad
⭐
10
Autograd (backpropagation, reverse-mode auto differentiation) in Nim
Pso For Neural Nets
⭐
9
Particle Swarm Optimizer For Neural Network Training
Qsnns
⭐
9
Quantization-aware training with spiking neural networks
Policy Gradient Network Arduino
⭐
9
Spikingtorch
⭐
9
A pytorch implementation of spiking neural networks and backpropagation through spikes
Brainz
⭐
8
Artificial Neural Network library written in Ruby
Dolores
⭐
8
🧠 A simple feedforward neural network
Neuralnetstudio
⭐
8
Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).
Bpnn Face Recognition For Qt
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8
👦 A Face Recognition System Based on BPNN(Back Propagation Neural Network) Developed by Qt.
Digit Recognition
⭐
8
Training an ANN and a CNN to recognize handwritten digits using back-propagation algorithm on MNIST data-set
Mnist_neural_network
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8
An neural network to classify the handwritten digits 0-9 for the MNIST dataset. No NN/ML libraries used.
Neuralnetwork
⭐
8
A simple lib that allows to make neural network
Go Neural Network
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7
Modifiable neural network
Feature Vis Yolov3
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7
Feature visualization tool for YOLOv3, a real-time objection detection algorithm using a deep convolutional network with a Darknet backbone. Visualizes performance attributes via saliency maps to identify how features in the input pixel space influence our network’s predictions in terms of classification and localization
Neural_network_from_scratch
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7
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
Rnnpresentation
⭐
7
RNNpresentation: A presentation about Recurrent Neural Network (RNN)
Aprendiendodeeplearning
⭐
7
Enlaces y recursos sobre redes neuronales y deep learning
Qneuralnet
⭐
7
Multi-layer backpropagation neural network implementation in Qt
Gnet
⭐
6
A neural network library written simply, efficiently and clearly. Supports convolutional NN.
All Optical Neural Networks
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6
Supporting code for "End-to-end optical backpropagation for training neural networks".
Encog
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6
Encog is a NodeJs ES6 framework based on the Encog Machine Learning Framework by Jeff Heaton.
Brain
⭐
6
neural network
Most Influential Data Science Research Papers
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6
"Data scientists are kind of like the new Renaissance folks, because data science is inherently multidisciplinary." ― John Foreman
Machine Learning Examples
⭐
6
Mnist Ai Up
⭐
6
Learning deep learning 😎 and neuroevolution 👾 ⭐
Bidirectional
⭐
6
Complete project for paper "Bidirectional Learning for Robust Neural Networks"
Neural Networks And Deep Learning Ko
⭐
5
Translation of Neural Networks and Deep Learning by Michael Nielsen
Backpropagation Neural Network For Multivariate Time Series Forecasting
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5
Backpropagation Neural Network for Multivariate Time Series Forecasting (multi input single output: 2 inputs and 1 output)
Spikingmoyf
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5
Spiking Neural Network
Gait Prop
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5
A biologically plausible learning rule derived from backpropagation of error
Bpnn
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5
Backpropagation Neural Network by java
Ocr
⭐
5
Optical character recognition using backpropagation with a 3-layer neural network
Pytorch Dni
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5
Decoupled Neural Interfaces Using Synthetic Gradients - under develeopment
Exercise Breast Cancer
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5
Python feed-forward neural network to predict breast cancer. Trained using stochastic gradient descent in combination with backpropagation.
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