Displaying 1 to 10 from 10 results

Deeplearning4J - Neural Net Platform in Java and Scala

Deeplearning4J is an open source, distributed neural net library written in Java and Scala. It integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. It provides versatile n-dimensional array class for Java and Scala.

Theano - Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs.

Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Its features include tight integration with NumPy, transparent use of a GPU, dynamic C code generation and lot more.

OpenCog - Framework to build Artificial Intelligence Programs

The OpenCog Framework is a platform to build and share artificial intelligence programs. It includes components for procedural and declarative knowledge representation (AtomSpace), task scheduling (CogServer), AI algorithm containers (MindAgents), connectors to instant messaging and virtual world systems, and other components. MindAgents and other add-ons explore a wide variety of AI techniques including evolutionary program learning (MOSES), natural language processing, and others.

Multi Touch Digit OCR With Matlab Neural Network Wpf Project

Multi Touch Digit OCR Project is a wpf project that works on multi touch devices but it works well on normal devices , this project uses matlab core , that creates 4 feed forward neural network and train them with Back Propagation Algorithm for detecting numbers that you draw .

Neural network - digit recognition

Digit recognition contain implementation of simple and effective implementation of neural network. Neural network is used to recognize handwritten digits - OCR system. Core functionality it is developed in C++ native programming language, STL, boost, GUI in C++ .NET.

Neural Networks Library

Neural networks Library by Sefnaj

Neural Network Basic

Neural Network Basic contain implementation of simple and effective implementation of neural network. Functionality it is developed in C++ native programming language, with use STL and Visual Studio C++ Express 2010.

Neural Cryptography in F#

This project is my magistracy resulting work. It is intended to be an example of using neural networks in cryptography. Hashing functions are chosen as the first step in this broad topic. Implementation language is F# running under .NET 4.0 with VS 2010 RC

Back-Propagation Neural Networks Simulation

This is simple Back-Propagation Neural Network simulation using C#. This code is a part of my "Supervised Neural Network" book written in 2006.