Search Results for "artificial intelligence algorithm"
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Showing 40 open source projects for "artificial intelligence algorithm"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Source code from the Research Institute for Signals, Systems and Computational Intelligence http://fich.unl.edu.ar/sinc
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Faum
Fast Autonomous Unsupervised Multidimiensional Classification
This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful. -
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Lush is a Lisp dialect with extensions for object-oriented and array-oriented programming. Lush is intended for prototyping numerically intensive applications and is designed for easy integration of existing C/C++/Fortran codes.
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is... -
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TXM
Unicode XML TEI text analysis platform
TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP... -
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Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
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PetaVision
Accelerated Open-Source Neuromorphic Computing
///////// NOTICE We have migrated to GitHub: https://petavision.github.io To clone an updated repository of the PetaVision codebase, please go to our page on GitHub. ///////// PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the... -
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ktree
clustering, machine learning, algorithms
This project has moved to github at http://lmwtree.devries.ninja. -
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MyNook
A machine learning system for supervised document classification
An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself. -
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Vedvarsha is an application for 2 purposes: 1. Handwariting script recognition that extracts recognized letters into documents. 2. OCR (Optical Character Recogniton) that works only for non-cursive and isolated characters. It depends upon libsyntactic,
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GamesCrafters is an undergraduate research group at the University of California, Berkeley. GAMESMAN is our software for building text & X11 apps for finite, 2-person abstract perfect-information games (e.g., TicTacToe & chess). We've authored 40+ games
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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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Python module to interface the CLIPS expert system shell library.
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TimeSleuth - Temporal Rule Discovery
Temporal and Causal Decision Rules
TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}. -
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Geeks Artificial Neural Network (G.A.N.N) is an open source project that started with the philosophy of being a new more advanced A.N.N that works as a platform for other applications. In other words, G.A.N.N should be considered as a "Black Box".
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GMM-GMR is a light package of functions in C/C++ to compute Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR). It allows to encode any dataset in a GMM, and GMR can then be used to retrieve partial data by specifying the desired inputs.
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SYRAH si propone di far emergere e rappresentare i concetti espressi per mezzo di un linguaggio naturale. SYRAH aims to discover and represent concepts expressed in natural languages. NLP, lemma, lemmario, italiano, rete, semantica, clustering, semantic
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Random Projection Trees is a recursive space partitioning datastructure which can automatically adapt to the underlying (linear or non-linear) structure in data. It has strong theoretical guarantees on rates of convergence and works well in practice.
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Easy-to-use platform-independent plugin API for the extraction of low-level features from audio data in PCM format, as required in the context of music information retrieval software.
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Concurrent vision processing system; Toolkit for easy implementation of software concurrent vision processing sub-system. Aimed at robotic applications w/best effort realtime. System includes: capture,processing and displaying.
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DigitalEyes is an OCR (Optical Character Recognizer) developed in C/Caml released under GNU GPL by SuM42, as a sophomore project in EPITA.
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FlexCRFs: A Flexible Conditional Random Fields Toolkit for Labeling and Segmenting Sequence Data (this includes a parallel implementation of CRFs called PCRFs to support training CRF models on massively parallel computer systems).
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META is a decision making software which aims are to track computer attackers, computer attacks and to help investigators finding useful elements.
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Its a model fitting framework which optimizes the model parameters to make the model output match the desired data.
