Search Results for "mac framework" - Page 27
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Showing 677 open source projects for "mac framework"
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JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
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Bamboo Engine
Game framework on top of Python, Panda3D and Twisted
Bamboo intends to be a complete end-to-end game framework for client/server applications using Twisted for data exchange, Panda3D for rendering and coded in Python. Support for PyPy/CPython may be considered at a later point. An Extreme/Agile Development model is in use to allow for emergent design (IE: changing requirements). Release is updated whenever a feature is added and all tests pass cleanly 100% -
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Four In Row Arena
Implement your player strategy and compete with other strategies.
A generic framework for Four in A Row or Five In A Row or X In A Row game, with the possibility to develop different strategies and compare them in tournaments. To implement more players, create new class inherited from PlayerStrategy, and implement the move() method to chose best move, by utilizing different methods provided with Table object. -
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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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A toolkit for the optical recognition of Psaltiki 19th century music notation. It is based on and requires the Gamera document image analysis framework (http://gamera.sf.net).
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This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
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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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Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
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Behaviours provide a way to quickly author reusable sequences of actions for use in the PaSSAGE framework, or any Neverwinter Nights module. The Behaviour Tool is a tool for the creation and management of behaviours.
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Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
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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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The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
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Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
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A python implementation of Fresnel, a display vocabulary for the Resource Description Framework (RDF). See http://www.w3.org/2005/04/fresnel-info/.
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Educational game framework supporting board games, strategy games, and other grid-based game boards. Currently uses Python/wxPython as the application language/library. C++ libs included to help create AI for the various games.
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FEAR is a development kit helping software engineers create advanced artificial intelligence in synthetic characters with simplicity and efficiency. The project includes reusable AI components, portable framework and interfaces to realtime 3D games.
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Excors is a natural language interpretation system (chatterbot framework) that uses XML and Python for natural language modules.
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Genetic Programming framework written in Python. Takes advantage of python\'s compiler to make things simple. Includes basic genetic operations (rank/roulette selection,crossover,mutation,steady state,elitistm ...)
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pySPACE
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due... -
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Nemotron 3 Nano
LL model providing reasoning and conversational capabilities
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 is a mid-sized open large language model created by NVIDIA to provide strong reasoning and conversational capabilities while maintaining efficient deployment requirements. The model contains roughly 30 billion parameters and is designed to balance performance and computational efficiency, making it suitable for developers building AI applications that cannot run extremely large models. It is trained from scratch and built using a hybrid architecture that... -
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DeepSeek-V3.2-Speciale
High-compute ultra-reasoning model surpassing model surpassing GPT-5
DeepSeek-V3.2-Speciale is the high-compute, ultra-reasoning variant of DeepSeek-V3.2, designed specifically to push the boundaries of mathematical, logical, and algorithmic intelligence. It builds on the DeepSeek Sparse Attention (DSA) framework, delivering dramatically improved long-context efficiency while preserving full model quality. Unlike the standard version, Speciale is tuned exclusively for deep reasoning and therefore does not support tool-calling, focusing its full capacity on... -
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DeepSeek-V3.2
High-efficiency reasoning and agentic intelligence model
DeepSeek-V3.2 is a cutting-edge large language model developed by DeepSeek-AI, focused on achieving high reasoning accuracy and computational efficiency for agentic tasks. It introduces DeepSeek Sparse Attention (DSA), a new attention mechanism that dramatically reduces computational overhead while maintaining strong long-context performance. Built with a scalable reinforcement learning framework, it reaches near-GPT-5 levels of reasoning and outperforms comparable models like DeepSeek-V3.1...
