Search Results for "cuda machine learning" - Page 33
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Showing 835 open source projects for "cuda machine learning"
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mlpy
Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. -
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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
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The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.
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PyPR - Python Pattern Recognition. A small collection of useful pattern recognition methods. The code is still in its early stages.
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An agent-based situated language learning simulation that focuses on lexical learning and grounding, featuring a unigram syntax structure and a CFG-based semantic grammar. Created as a MSc thesis project, using python.
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The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.
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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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Onyx is for rapid prototyping and large-scale experimentation on advanced machine-learning algorithms with an emphasis on algorithms for online or streaming analysis, modeling, and classification.
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Monte is machine learning in pure Python. Monte's focus is the construction of gradient based learning machines from many small components.
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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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NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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Spider that recollects data from MySpace Social Network. At now, it is only designed to extract information from native american people because it is used for a social science study in the UNAM (Universidad Nacional Autónoma de México).
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A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
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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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Python Machine learning library with multi-core support. Wraps existing ML libraries in order to be able to run and analyse experiments with one front-end API. Currently supports MLP, GA, GP, ESN and RBF algorithms.
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pygpr is a collection of algorithms that can be used to perform Gaussian process regression and global optimization.
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Definir un entorno (medio ambiente) y a micro-organismos (gunus) que vivan en el y se desarrollen es el objeto de este proyecto.
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This project is developing a modular framework for constructing machine intelligences. The modular approach allows for both rapid development of simple AI's and also construction of larger and more general learning based engines.
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VFML -- Very Fast Machine Learning toolkit. A collection of tools, learners, and APIs for working with high-speed data streams and very large data sets.