Open Source Linux Data Visualization Software - Page 10
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AI-Powered Identity GovernanceDefine governance policies, manage access, and optimize licenses with unified visibility across every identity, app, and file.
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A privacy-first API that predicts global consumer preferencesThrough our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things.
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BAT.jl
A Bayesian Analysis Toolkit in Julia
Welcome to BAT, a Bayesian analysis toolkit in Julia. BAT.jl offers a variety of posterior sampling, mode estimation and integration algorithms, supplemented by plotting recipes and I/O functionality. BAT.jl originated as a rewrite/redesign of BAT, the Bayesian Analysis Toolkit in C++. BAT.jl now offer a different set of functionality and a wider variety of algorithms than its C++ predecessor. -
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BERT
Connector for Excel and the programming languages R and Julia
BERT is a tool for connecting Excel with the statistics language R. Specifically, it’s designed to support running R functions from Excel spreadsheet cells. In Excel terms, it’s for writing User-Defined Functions (UDFs) in R. All you have to do is write the function. Everything else – loading the function into Excel, managing parameters, and handling type conversion – is done automatically for you. It really could not be any easier. BERT also has a console that you can use to control Excel in real time, right from your R code. And (if you want), you can call R functions from VBA as well. -
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. Mostly notorious is null-hypothesis significance testing (NHST) based on p-values. -
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BetaML.jl
Beta Machine Learning Toolkit
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its implementation. Thanks to its JIT compiler, Julia is indeed in the sweet spot where we can easily write models in a high-level language and still have them running efficiently. -
Powering the next decade of business messaging | Twilio MessagingXBuild unique experiences across SMS, MMS, Facebook Messenger, and WhatsApp – with our unified messaging APIs.
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BizCharts
Powerful data visualization library based on G2 and React
BizCharts is Alibaba's general charting component library, dedicated to creating efficient, professional and convenient data visualization solutions in the middle and backend of enterprises. Based on the React charting library packaged by G2 and G2Plot, it has experienced three years of baptism in Alibaba's complex business scenarios. In terms of convenience, ease of use, and richness, it satisfies the business implementation of conventional charts and highly customized charts. After years of accumulation and continuous polishing, BizCharts 4.0 has been newly upgraded; in addition to having a flexible graphics syntax, it has added an interactive syntax and a better animation experience. At the same time, it enhances the React coding ability, and the writing is freer. The built-in encapsulation of responsive chart g2-plot works out of the box and complements the atomic capabilities of BizCharts to keep moving forward on the visual path of flexibility and ease of use. -
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Bukdu.jl
Bukdu is a web development framework for Julia
Bukdu.jl is a web development framework for Julia. -
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CUDA.jl
CUDA programming in Julia
High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will happen automatically when you install the package using Julia's package manager. -
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CausalityTools.jl
Algorithms for detecting associations, dynamical influences
CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can think of. For example, we offer the generic SurrogateTest, which is fully compatible with TimeseriesSurrogates.jl, and the LocalPermutationTest for conditional independence testing. -
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Charts.css
Open source CSS framework for data visualization
Charts.css is a modern CSS framework. It uses CSS utility classes to style HTML elements as charts. No dependencies. 72kb file size. Less than 6kb gzipped file size! Visualization helps end-users understand data. Charts.css help frontend developers turn data into beautiful charts and graphs using simple CSS classes. The data is structured using semantic HTML tags and styled using CSS classes which change the visual representation displayed to the end-user. The framework offers developers flexibility. You choose what components to display and how to style them. Each component offers several CSS classes and CSS variables to customize your style. The key feature is the ability to customize everything using basic CSS. Frontend developers can target any HTML element and customize it. This philosophical guideline is what makes the framework so flexible, easy, and fun to use. -
Streamline Hiring with Skill AssessmentsCanditech offers innovative, cheat-proof skill assessments and job simulations to transform your hiring process. From technical skills to soft skills, we help you assess candidates on actual job performance. With over 500 customizable tests and powerful video interview features, you can evaluate real-world capabilities, streamline your hiring, and reduce biases. Whether you’re hiring for remote roles, mass hiring, or looking to expand your diversity pool, Canditech’s data-driven platform ensures the right candidates are chosen for the job every time.
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Checkmate
Checkmate is an open-source, self-hosted tool
Checkmate is an open-source, self-hosted infrastructure monitoring platform that provides real-time visibility into server health, uptime, response times, and incident activity through a modern web interface. The application continuously checks whether websites and services are accessible and performing optimally, generating alerts and reports when availability or performance degrades. It supports detailed infrastructure monitoring through an optional agent called Capture, which collects hardware metrics such as CPU, memory, disk usage, and temperature from remote machines. The system is designed to scale, having been stress-tested with more than a thousand active monitors without major performance issues. Checkmate also includes incident tracking and notification capabilities so teams can quickly respond to outages or anomalies. Overall, the platform serves as a comprehensive, developer-friendly alternative to commercial uptime and infrastructure monitoring tools. -
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Chokidar
Minimal and efficient cross-platform file watching library
Chokidar is a solution for all the users of Node.js fs.watch who are tired of it not reporting filenames on MacOS and events at all when using editors like Sublime on MacOS. Node.js fs.watch often reports events twice, emits most changes as rename, and it does not provide an easy way to recursively watch file trees nor supports recursive watching on Linux. Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build tool), it is now used in Microsoft's Visual Studio Code, gulp, karma, PM2, browserify, webpack, BrowserSync, and many others. It has proven itself in production environments. Chokidar does still rely on the Node.js core fs module, but when using fs.watch and fs.watchFile for watching, it normalizes the events it receives, often checking for truth by getting file stats and/or dir contents. -
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Clapeyron
Framework for the development and use of fluid-thermodynamic models
Welcome to Clapeyron! This module provides both a large library of thermodynamic models and a framework for one to easily implement their own models. Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC. -
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ClickVisual
Log analytic and data visualize platform built on clickhouse
ClickVisual is a lightweight browser-based logs analytics and logs search platform for ClickHouse. -
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ComponentArrays.jl
Arrays with arbitrarily nested named components
The main export of this package is the ComponentArray type. "Components" of ComponentArrays are really just array blocks that can be accessed through a named index. This will create a new ComponentArray whose data is a view into the original, allowing for standalone models to be composed together by simple function composition. In essence, ComponentArrays allow you to do the things you would usually need a modeling language for, but without actually needing a modeling language. The main targets are for use in DifferentialEquations.jl and Optim.jl, but anything that requires flat vectors is fair game. -
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CondaPkg.jl
Add Conda dependencies to your Julia project
Add Conda dependencies to your Julia project. This package is a lot like Pkg from the Julia standard library, except that it is for managing Conda packages. Conda dependencies are defined in CondaPkg.toml, which is analogous to Project.toml. CondaPkg will install these dependencies into a Conda environment specific to the current Julia project. Hence dependencies are isolated from other projects or environments. Functions like add, rm, status exist to edit the dependencies programmatically. Or you can do pkg> conda add some_package to edit the dependencies from the Pkg REPL. -
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CoordinateTransformations.jl
A fresh approach to coordinate transformations
CoordinateTransformations is a Julia package to manage simple or complex networks of coordinate system transformations. Transformations can be easily applied, inverted, composed, and differentiated (both with respect to the input coordinates and with respect to transformation parameters such as rotation angle). Transformations are designed to be light-weight and efficient enough for, e.g., real-time graphical applications, while support for both explicit and automatic differentiation makes it easy to perform optimization and therefore ideal for computer vision applications such as SLAM (simultaneous localization and mapping). -
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CounterfactualExplanations.jl
A package for Counterfactual Explanations and Algorithmic Recourse
CounterfactualExplanations.jl is a package for generating Counterfactual Explanations (CE) and Algorithmic Recourse (AR) for black-box algorithms. Both CE and AR are related tools for explainable artificial intelligence (XAI). While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs. -
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DataStructures.jl
Julia implementation of Data structures
Julia implementation of Data structures. -
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DiffEqBayes.jl
Extension functionality which uses Stan.jl, DynamicHMC.jl
This repository is a set of extension functionality for estimating the parameters of differential equations using Bayesian methods. It allows the choice of using CmdStan.jl, Turing.jl, DynamicHMC.jl and ApproxBayes.jl to perform a Bayesian estimation of a differential equation problem specified via the DifferentialEquations.jl interface. -
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DiffOpt.jl
Differentiating convex optimization programs w.r.t. program parameters
DiffOpt.jl is a package for differentiating convex optimization programs (JuMP.jl or MathOptInterface.jl models) with respect to program parameters. Note that this package does not contain any solver. This package has two major backends, available via the reverse_differentiate! and forward_differentiate! methods, to differentiate models (quadratic or conic) with optimal solutions. Differentiable optimization is a promising field of convex optimization and has many potential applications in game theory, control theory and machine learning. Recent work has shown how to differentiate specific subclasses of convex optimization problems. But several applications remain unexplored. With the help of automatic differentiation, differentiable optimization can have a significant impact on creating end-to-end differentiable systems to model neural networks, stochastic processes, or a game. -
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Distributions.jl
A Julia package for probability distributions and associated functions
A Julia package for probability distributions and associated functions. -
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DynamicQuantities.jl
Lightweight + fast physical quantities in Julia
DynamicQuantities defines a simple statically-typed Quantity type for Julia. Physical dimensions are stored as a value, as opposed to a parametric type, as in Unitful.jl. This can greatly improve both runtime performance, by avoiding type instabilities, and startup time, as it avoids overspecializing methods. -
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EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing native Julia code and generating relaxations on a wide variety of user-defined functions have been included. Currently, EAGO supports problems that have a priori variable bounds defined and have differentiable constraints. -
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Excalidraw MCP
Fast and streamable Excalidraw MCP App
Excalidraw-MCP is an open-source Model Context Protocol (MCP) application and server that connects the visual power of Excalidraw’s hand-drawn diagram editor with AI-driven workflows, enabling agents like Claude, ChatGPT, VS Code, and other MCP-compatible hosts to generate and manipulate diagrams programmatically. Rather than being just a static whiteboard, Excalidraw-MCP serves diagrams in real time using an MCP backend and streams interactive visual output back to the client, letting AI tools create shapes, connectors, text, and entire diagrams as part of conversational or task-based sessions. Its design supports fast, streamable rendering with smooth viewport control and optional fullscreen editing so that diagrams feel live and fluid as they evolve. Users can deploy it locally or via services like Vercel, then configure their MCP host to point at the Excalidraw-MCP endpoint, so prompts like “draw an architecture diagram” yield immediate visual results within chat. -
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EzXML.jl
XML/HTML handling tools for primates
EzXML.jl is a package to handle XML/HTML documents for primates. This package depends on libxml2, which will be automatically installed as an artifact via XML2_jll.jl if you use Julia 1.3 or later. Currently, Windows, Linux, macOS, and FreeBSD are now supported.
