Search Results for "backpropagation network"

Karpathy-Inspired Claude Code Guidelines is a curated learning and experimentation repository inspired by the work and teaching philosophy of Andrej Karpathy, designed to help learners build practical competence in deep learning, neural networks, and AI infrastructure. The project organizes a progressive path through exercises, notebooks, code examples, and practical mini-projects that echo Karpathy’s approach to “learning by doing,” where students build core concepts from first principles...

Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.

CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. ...

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.

Code of this library is partialy based on myCNN MATLAB class written by Nikolay Chemurin.

Cognity is an object-oriented neural network library for Java. It's goal is to provide easy-to-use, high level architecture for neural network computations along with reasonable performance.

Syntactic is a simple C++ library for constructing general Neural networks. For now the library supports creation of multi layered networks for the Feedforward Backpropagation algorithm as well as Time Series Networks. More will be implemented soon.

3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar"

This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.

Lightweight backpropagation neural network in C++. The project provides a class implementing a feedforward neural network, and a class for easily train it. It is highly customizable to manage your problem and comes with a simple graphical interface.

Lightweight backpropagation neural network in C. Intended for programs that need a simple neural network and do not want needlessly complex neural network libraries. Includes example application that trains a network to recognize handwritten digits.