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Showing 24 open source projects for "fast"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Practically Random
statistical tests & psuedo- random number generators (RNGs, PRNGs)
Randon number generation & testing. The best suite of statistical tests for fast PRNGs anywhere. Multithreaded for speed, command line tools for automation, no upper limit on data size. Also, a variety of C++ pseudo-random number generators with well designed interfaces aimed at practical uses, not just research. -
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Data Envelopment Analysis using Stata
Unified Data Envelopment Analysis commands for Stata
...Version 2.0 is a major update centered on a unified dea command for Stata 16 or later. It consolidates sixteen DEA model families into one interface, keeps backward compatibility with the original inputs = outputs syntax, and adds a fast Mata two-phase revised simplex engine alongside Stata's LinearProgram() IPM engine. The package supports radial technical efficiency (CCR/BCC), SBM, additive model, radial and SBM super-efficiency, multiplier form, directional distance function, cost, revenue, profit, allocative efficiency, FDH, imprecise DEA, undesirable outputs, SBM with undesirable outputs, and congestion analysis. ... -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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stkpp
C++ Statistical ToolKit
STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Random
Generation random numbers, words and elements
The application supports Russian and English languages. An application for generating random numbers, words and selecting a random element from a list. The simple interface ensures fast and convenient user interaction. - Random numbers: generation is possible in any range. - Random words: the application's vocabulary is about 10,000 words and will increase in future versions. - Random element: the number of elements in the list is not limited, all have an equal probability of selection. -
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VAERity
Uncovering truth in data
VAERity is a free, open source tool to graphically explore the VAERS data set. It aims to eventually expand in scope to allow fast querying of arbitrary large datasets. It utilizes vaex and pandas as required to provide a balance of speed and query flexibility. -
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Chuck Coleman's SAS Codes
SAS Codes
SAS codes for LMG variable importance, Box-Cox transformation including interactions. Documentation and PowerPoint slides. Directories under "Files" with descriptions: NESUG 2014: "A Fast, High-Precision Implementation of the Univariate One-Parameter Box-Cox Transformation Using the Golden Section Search in SAS/IML®" SESUG 2017: "Decomposing the R-squared of a Regression Using the Shapley value in SAS®" SESUG 2019: "Conditionally Executing Data Steps and Statements Based on the Presence of Variables in a SAS® Dataset" GASP 2020: "Online Winsorization of the Survey of Construction’s Price Estimates" My SESUG 2015 materials can also be found in my project "constrainingarrays" at https://sourceforge.net/projects/constrainingarrays/. -
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gsasnp2
PubMed ID: 29562348 / DOI: 10.1093/nar/gky175
* GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values and outputs pathway genesets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways. * Article: SYoon, HCTNguyen, YJYoo, JKim, BBaik, SKim, JKim, SKim, DNam, "Efficient pathway enrichment and network analysis of GWAS summary data... -
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Community Detection Modularity Suite
Suite of community detection algorithms based on Modularity
...Newman, Physical Review E, 74(3):036104, 2006. [3] B. Ball et al, An efficient and principled method for detecting communities in networks, 2011. The suite is based upon the fast community algorithm implemented by Aaron Clauset <aaron@cs.unm.edu>, Chris Moore, Mark Newman, and the R IGraph library Copyright (C) 2007 Gabor Csardi <csardi@rmki.kfki.hu>. It also makes of the classes available from Numerical Recipies 3rd Edition W. Press, S. Teukolsky, W. Vetterling, B. Flanne -
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Statistics Calculator
Fast and Efficient Statistics Calculator
A simple program that calculates the mean, mode, range, quartiles and standard deviation of a set of input numbers. -
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GADfit
Global nonlinear optimization with automatic differentiation
...GADfit is a Fortran implementation of global nonlinear curve fitting, based on a modified Levenberg-Marquardt algorithm. Global fitting refers to fitting many datasets simultaneously with some parameters shared among the datasets. The fitting procedure is very fast and accurate thanks to the use of automatic differentiation. The model curves (fitting functions) can be of essentially arbitrary complexity. This includes any nonlinear combination of elementary and special functions, single and/or double integrals, and any control flow statement allowed by the programming language. See the latest user guide under Files. -
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
...Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++. -
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mathSuite
Powerful Calculus Environment and Matrices Handling Engine
mathSuite is a very powerful Mathematical Suite which deals principally with complex algebric and geometric operations. It is powered by the fabulous ExprEval C Parser. The main purpose of this project is fast math-oriented algorithm virtualization, with an optimized direct text interface. Also it gives you a very powerful and fast Calculus Environment which let you handle easily interchangeable variable lists, matrices, LOGS and Settings Layouts with optimized Items Lists Managing Engine. You'll also be able to execute your own scriptfiles with a basic math-oriented beta script language. ... -
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QPNet
Synchronous Petri Nets' emulator
QPNet (Quick Petri Net) is a fast Petri Nets' emulator, created by students of Moscow State Technical University of Radio Engineering, Electronics and Automation. It brings benefits for the educational process, while being under further development and extension. QPNet это быстрый эмулятор сетей Петри, созданный студентами МИРЭА. Он применяется в учебном процессе, а так же продолжает разрабатываться и эволюционировать. -
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KeplerDB
Timeseries databases management system
KeplerDB is a temporal database to store time/value entries where the type of value could be integer, float/double, boolean and string. KeplerDB is dedicated to be scalable and to create clusters of server allowing the user to analyse and store massing amount of data to monitor systems like computers, clusters, building and captors or financial systems like markets and accounts. The user can use KeplerDB to make data analysis on enormous amount of data (statistics and modelling). -
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IterInt is a numerical integration package that implements iterated numerical integration methods. Iterated methods can be used to compute low dimensional (less than ten, for example) integration problems to get very accurate results.
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Statistics modules in Perl Data Language, with a quick-start guide for non-PDL people. They make the PDL shell work like R, but with PDL threading (fast automatic iteration) of procedures including t-test, linear regression, and k-means clustering.
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libfgen
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported. -
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Binomial Distribution Calculator
A simple to use Binomial Distribution Calculator.
A simple to use binomial distribution calculator: Just enter the sufficient data like number of trials, probability and number of successes. You can display the calculated data in a table or even graphically. Simultaneously, this application computes the expected value and the standard deviation. To use this app you need to have .NET Framework 4 installed. Contact me: lambdapew-dev@yahoo.de -
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The Automated Parameter Estimation and Model Selection Toolkit is a fast, parallelized MCMC engine written in C for Bayesian inference (parameter estimation and model selection).
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Nen
neural network implementation in java
3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar" -
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GpaNom is a simple command line GPA calculator, written in C, with the goal of being fast and precise.
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. ...
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