Projects sharing features with Graph

GO Implementation of Entropy Measures

GoStats is a go library for math statistics mostly used in ML domains, it covers most of the statistical measures functions.

tiny linear interpolation library for go

2D triangulation library. Allows translating lines and polygons (both based on points) to the language of GPUs.

Streaming approximate histograms in Go

Exponentially Weighted Moving Average algorithms for Go.

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.

Weighted PageRank implementation in Go

:wink: :cyclone: :strawberry: TextRank implementation in Golang with extendable features (summarization, phrase extraction) and multithreading (goroutine).

Gonum is a numerical computing library for the Go programming language, providing a collection of packages for scientific computing, linear algebra, statistics, and optimization. It functions as a framework for performing complex numerical computations and solving systems of linear equations. The project includes a dedicated graph analysis framework for modeling network graphs and solving connectivity and pathfinding problems. It also provides a statistical analysis toolkit for computing descriptive and inferential statistics and estimating mixture entropy. The library's capability surface c

A repository for plotting and visualizing data

A well tested and comprehensive Golang statistics library package with no dependencies.

Package goraph implements graph data structure and algorithms.

tools for working with streams of data

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Package to do Bradley-Terry Model pairwise compairsons

This repository serves as an educational collection of interactive notebooks and code examples designed to demonstrate fundamental machine learning and deep learning concepts. It provides a structured environment for exploring data science workflows, ranging from basic numerical computing and statistical analysis to the construction of complex neural network architectures. The project distinguishes itself through a focus on hands-on experimentation, offering practical implementations for tasks such as computer vision, natural language processing, and statistical simulation. Users can engage w

Modular and modern graph-theory algorithms framework in Java

A 3D chart library for Java applications (JavaFX, Swing or server-side).

A general classifier module to allow Bayesian and other types of classifications. A fork of cardmagic/classifier.

JGraphX

Scientific library for the D programming language