Search Results for "python neural" - Page 7
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Showing 186 open source projects for "python neural"
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
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Neural Libs
Neural network library for developers
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. -
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MetaNet
Free portable library for meta neural network research
MetaNet provides free library for meta neural network research. MetaNet library contain feed-forward neural net realisation and several integrated dataset (MNIST). -
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LWPR
Locally Weighted Projection Regression (LWPR)
..., Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005). [2] Stefan Klanke, Sethu Vijayakumar and Stefan Schaal, A Library for Locally Weighted Projection Regression, Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). More details and usage guidelines on the code website. -
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Simple program for artificial neural network users. Right now the program can manipulate with Feed forward back propagation network.
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mullpy
Multilabel-learning library built on python
Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3. -
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read...
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tnets
Theano-based (Deep) Neural Networks for Speech Research
Alpha tool build on the top of Theano and delibaretly tuned for ASR/NLP tasks. -
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BetBoy
Using neural networks to predict outcomes of football matches
Predicting outcomes of matches using neural networks,simulations,automatic bets selector,automatic/manual database updates How to use instructions: https://sourceforge.net/p/betboy/wiki/Home/ Video presentation: http://www.youtube.com/watch?feature=player_embedded&v=I2C5TlBSB6w http://www.youtube.com/watch?feature=player_embedded&v=hZ00br89_l8 http://www.youtube.com/watch?feature=player_embedded&v=844iwI8zBZk -
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Neural Diversity Machines
A Hybrid Neural Network that implements a diverse transfer functions
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RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition. full installation and usage instructions given at http://sourceforge.net/p/rnnl/wiki/Home/
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This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
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The main intention of this project is to support the SNNS (Stuttgart Neural Net Simulator) with patches, bugfixes, tools and add on developments. Second target is to publish useful links and information about the SNNS.
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NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
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Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
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A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.
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Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence
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Brainlab is a Python toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NeoCortical Simulator (NCS).
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PolyPlanet is an evolutionary playground inspired by Polyworld. It uses genetic algorithms to evolve the world and its inhabitants. Current inhabitants include PolyPlants, PolyTrees, and PolyDudes that have neural network brains which also evolve.
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Aureservoir is an open-source C++ library for analog reservoir computing neural networks (echo state networks) with bindings to various scientific computing packages.
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Artificial Intelligence program - keyword based chat, personal voice in/out, animated 3D character, natural language recognition and translation, neural network based strong AI, personality, tone recognition
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AKIRA aims to create a C++ development framework to build cognitive architectures and complex artificial intelligent agents.Features:KQML,Fuzzy Logic,Neural Net,Fuzzy Cognitive Maps and DIPRA (a distributed BDI - Belief Desire Intention goals model)
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We experiment with Evolution of Artifical Neural Networks, combining the two fields of Evolutionary Computation and ANNs. Our methods are applied to a variety of interesting problems. To learn more, click on "Home Page", "Mail", or "Files".
