52 Open Source Backpropagation Software Projects
Free and open source backpropagation code projects including engines, APIs, generators, and tools.
Ahmedbesbes Neural Network From Scratch 221 ⭐
Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?
Machine_learning_2018 117 ⭐
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
Fotisk07 Deep Learning Coursera 112 ⭐
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
Selfdrivingcar 93 ⭐
A collection of all projects pertaining to different layers in the SDC software stack
Theoretical Proof Of Neural Network Model And Implementation Based On Numpy 65 ⭐
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。
Rcnn_mdp 63 ⭐
Code base for solving Markov Decision Processes and Reinforcement Learning problems using Recurrent Convolutional Neural Networks.
Machine Learning In Python Workshop 59 ⭐
My workshop on machine learning using python language to implement different algorithms
Neuralduino 34 ⭐
The only dynamic and reconfigurable Artificial Neural networks library with back-propagation for arduino
Rubixml Sentiment 36 ⭐
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
Swiftsimpleneuralnetwork 29 ⭐
A simple multi-layer feed-forward neural network with backpropagation built in Swift.
Diffhask 26 ⭐
DSL for forward and reverse mode automatic differentiation in Haskell. Port of DiffSharp.
Newbie_neural_network_practice 27 ⭐
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：
Artificialintelligenceengines 26 ⭐
Computer code collated for use with Artificial Intelligence Engines book by JV Stone
Whitebox Part1 22 ⭐
In this part, i've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
Minimalistic Multiple Layer Neural Network From Scratch In Python 21 ⭐
Minimalistic Multiple Layer Neural Network from Scratch in Python.
Differential Machine Learning Notebooks 27 ⭐
Implement, demonstrate, reproduce and extend the results of the article 'Differential Machine Learning' (Huge & Savine, 2020), and cover implementation details left out of the working paper
Recurrent JS 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.
Learning Lab C Library 13 ⭐
This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constatly updated
Appendices 12 ⭐
Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production
Computational Graph 10 ⭐
Efficiently performs automatic differentiation on arbitrary functions. Basically a rudimentary version of Tensorflow.
Rnn Rc Chaos 13 ⭐
RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.