Search Results for "statistics algebra"
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Showing 34 open source projects for "statistics algebra"
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
...The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. The repository includes Jupyter notebooks with explanations and examples that demonstrate how these mathematical principles relate to real machine learning applications. Each section introduces theoretical concepts and then illustrates them through practical coding examples to reinforce understanding. ... -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
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SymPy
A computer algebra system written in pure Python
SymPy is an open source Python library for symbolic mathematics. Its goal is to become a full-featured computer algebra system (CAS) while maintaining the simplicity of its code. Written entirely in Python, SymPy is easy to use, comprehensible and easily extensible. It’s also very lightweight as it solely depends on mpmath, a pure Python library for arbitrary floating point arithmetic. SymPy has participated in every Google Summer of Code since 2007 and because of this has continuously... -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
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Gonum
Set of numeric libraries for the Go programming language
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more. Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. ... -
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SciPy
SciPy library main repository
This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. ... -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
...The pre-reqs refresher days are asynchronous, so you can go through the material on your own time. You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. Then, you will cover linear algebra, calculus and probability & statistics. The topics covered on these days were carefully chosen based on what you need for the comp neuro course. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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Criterial
The package for statistical data analysis and applied mathematics
Putting truth before show-off. The high performance open source package for statistical data analysis and applied mathematics Criterial is an add-in for all desktop versions of the LibreOffice Calc, Apache OpenOffice spreadsheets on any operating systems. Contains user experience and the best ideas of projects AtteStat and StatAnt. Completely free. No donation required. Criterial comes with absolutely no warranty. The software is not certified for use in healthcare. Please do not use... -
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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. -
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Agena
Agena is an interpreted procedural programming language.
Agena is an easy-to-learn procedural programming language designed for science, scripting, and many other applications. Binaries are available for Windows, Linux, Solaris, OS/2, Mac OS X, Raspberry Pi and DOS. -
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sequoia-dap
SEQUOIA ocean data assimilation platform (a SIROCCO suite tool)
***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite... -
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DataMelt
Computation and Visualization environment
DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. ... -
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PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
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Mathematics
Accumulation of mathematical knowledge, matrix numerical optimization
Mathematics is a comprehensive collection of notes, resources, and references spanning a wide range of mathematical topics. The repository organizes material across pure and applied mathematics, including calculus, linear algebra, probability, statistics, and optimization. It also extends into computational and algorithmic applications of mathematics, making it a useful reference for both academic study and practical problem-solving. The goal is to provide learners, researchers, and developers with a consolidated source of foundational and advanced mathematical concepts. ... -
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Machine Learning cheatsheets Stanford
VIP cheatsheets for Stanford's CS 229 Machine Learning
...The repository includes summaries covering areas such as supervised learning, unsupervised learning, deep learning, and optimization techniques. In addition to machine learning algorithms, it also contains refresher materials on mathematical prerequisites including probability theory, statistics, linear algebra, and calculus. These cheat sheets are designed to serve as quick reference guides that students can use while studying or reviewing machine learning material. -
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TheoremJS
A Math library for computation in JavaScript
TheoremJS is a mathematical framework that is packed up with tons of useful mathematical functions. It is composed of functions in most mathematical fields such as algebra, number theory, statistics, etc... It was designed to fit your need, whatever you are trying to do. With TheoremJS, you won't feel the need of running the code on a server, you can run it right on the browser, or on a NodeJS notebook (Jupyter like). Even though we loose performances with BigNumber, our algorithms are well-engineered and ensure decent performances on every device. ... -
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Awesome Math
This is the Curriculum for "How to Learn Mathematics Fast"
This repository is a curated roadmap for learning the core mathematics used in computer science, machine learning, and data science without getting lost in unnecessary detours. It organizes topics like algebra, calculus, linear algebra, probability, and statistics into a pragmatic sequence that favors intuition and problem-solving over purely formal proofs. The materials emphasize short, high-leverage resources—video lectures, concise notes, and hands-on exercises—that help you build momentum quickly. It also suggests checkpoints and practice ideas so you can test comprehension and move forward with confidence. ... -
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...Contact: Louis-Noel Pouchet <pouchet@cse.ohio-state.edu> Tomofumi Yuki <tomofumi.yuki@inria.fr> PolyBench is a benchmark suite of 30 numerical computations with static control flow, extracted from operations in various application domains (linear algebra computations, image processing, physics simulation, dynamic programming, statistics, etc.). PolyBench features include: - A single file, tunable at compile-time, used for the kernel instrumentation. It performs extra operations such as cache flushing before the kernel execution, and can set real-time scheduling to prevent OS interference...
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...This sourceforge project contains only old historical versions of the software. SciPy is package of tools for science and engineering for Python. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.
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Universal Java Matrix Package
sparse and dense matrix, linear algebra, visualization, big data
The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra such as matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported, too. The Universal Java Matrix Package provides various visualization methods, import and export filters for a large... -
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Math Processor
Math Processor is a general purpose programable math engine.
The design and code of Math Processor have been explained at: http://www.codeproject.com/Articles/500327/Building-a-General-Purpose-Interpreter-Math-Engine Math Processor solves problems relating to algebra, calculus, Boolean logic, statistics, number theory, geometry, trigonometry and other allied disciplines. It supports a simple interpreted language. It also has some plotting capabilities. You can use MP as a standalone calculating engine or you can use it as a C# .dll library in your own programs. The design of MP makes it very easy to embed it in any .Net project. -
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SCaVis
Scientific Computation and Visualization Environment
SCaVis is an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential... -
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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....
