Search Results for "open-vm-tools" - Page 2
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Showing 2513 open source projects for "open-vm-tools"
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CategoricalArrays.jl
Arrays for working with categorical data
This package provides tools for working with categorical variables, both with unordered (nominal variables) and ordered categories (ordinal variables), optionally with missing values. -
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Personal Management System
Your web application for managing personal data
...Additionally, writing extensions is not too hard, depending on the logic required. Anyone with development knowledge can pretty much write their own extensions for personal needs. Keep a track of your personal goals. You can use tools to keep track of your goals progress or use the payments submodule to keep an eye of the money amount that you want to collect for something. Add any personal note to the desired category. Here, you can keep any small information that you need; it can be either quick notes from phone calls, a bunch of information collected all around different pages, or some links to things that you want to check somewhere later in the future. -
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ClimateTools.jl
Climate science package for Julia
Climate analysis tools in Julia. ClimateTools.jl is a collection of commonly-used tools in Climate science. Basics of climate field analysis are covered, with some forays into exploratory techniques associated with climate scenario design. The package is aimed to ease the typical steps of analysis of climate models outputs and gridded datasets (support for weather stations is a work-in-progress). -
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Digital Earth Australia notebooks
Repository for Digital Earth Australia Jupyter Notebooks
The knowledge hub brings together information about Digital Earth Australia’s products and services, allowing you to utilize our free and open-source satellite imagery archive. Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products. ... -
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PowerSystems.jl
Data structures in Julia to enable power systems analysis
The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing. -
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QuantumClifford.jl
Clifford circuits, graph states, and other quantum Stabilizer tools
A Julia package for working with quantum stabilizer states and Clifford circuits that act on them. Graphs states are also supported. The package is already very fast for the majority of common operations, but there are still many low-hanging fruits performance-wise. See the detailed suggested readings & references page for background on the various algorithms. -
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Karpor
World's most promising Kubernetes Visualization Tool
Karpor is Intelligence for Kubernetes. It brings advanced Search, Insight and AI to Kubernetes. It is essentially a Kubernetes Visualization Tool. With Karpor, you can gain crucial visibility into your Kubernetes clusters across any clouds. -
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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. -
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Sysdig
Linux system exploration and troubleshooting tool
...Gain deep insight with container and Kubernetes monitoring that is fully Prometheus compatible. Validate compliance against standards like PCI, NIST and SOC2 for containers, hosts, Kubernetes and cloud. Sysdig created Falco, the open standard for runtime threat detection for containers, hosts, Kubernetes and cloud. -
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Calculus.jl
Calculus functions in Julia
The Calculus package provides tools for working with the basic calculus operations of differentiation and integration. You can use the Calculus package to produce approximate derivatives by several forms of finite differencing or to produce exact derivatives using symbolic differentiation. You can also compute definite integrals by different numerical methods. -
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PySR
High-Performance Symbolic Regression in Python and Julia
PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective. Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. -
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beautiful-mermaid
Render Mermaid diagrams as beautiful SVGs or ASCII art
beautiful-mermaid is a styling and rendering toolkit built to produce visually enhanced diagrams from Mermaid syntax, aiming to bridge the gap between simple technical diagrams and rich, presentation-ready visualizations, all while preserving the lightweight text-to-diagram workflow that Mermaid offers. Instead of plain, utilitarian shapes and lines, Beautiful Mermaid applies themes, typography enhancements, color palettes, and layout optimizations so diagrams look polished and professional... -
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MIDI Visualizer
A small MIDI visualizer tool, using OpenGL
MIDIVisualizer is a cross-platform application that renders real-time visualizations of MIDI files using OpenGL. Inspired by the look of rhythm games and piano roll editors, it offers smooth animations and customizable themes to turn MIDI sequences into captivating graphical performances. It works as both a live visualizer and a tool to export visuals into video, making it ideal for musicians, VJs, and creators who want to produce visually engaging content synced to their compositions. -
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DataFrames.jl
In-memory tabular data in Julia
...It provides a familiar, flexible, and efficient interface for handling datasets, making it easy to load, manipulate, join, and analyze structured data. With syntax inspired by data frames in R and pandas in Python, it offers intuitive tools while taking advantage of Julia’s speed and type system. The package is actively maintained by the JuliaData community, with contributions from over 200 developers worldwide. It is widely used for data science, research, and production applications, supported by extensive documentation, tutorials, and a free Julia Academy course. ... -
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Checkmate
Checkmate is an open-source, self-hosted tool
...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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Data Formulator
Create rich visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data transformation barriers via LLMs' code generation ability. However, these systems do not work well for iterative visualization authoring, because they often require analysts to provide, in a single turn, a text-only prompt that fully describes the complex visualization task to be performed, which is unrealistic to both users and models in many cases. ... -
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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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Functors.jl
Parameterise all the things
Functors.jl provides tools to express a powerful design pattern for dealing with large/ nested structures, as in machine learning and optimization. For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step. -
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FinEtools.jl
Finite Element tools in Julia
FinEtools is a package for basic operations on finite element meshes: Construction, modification, selection, and evaluation of quantities defined on a mesh. Utilities are provided for maintaining mesh-based data (fields), for defining normals and loads, for working with physical units and coordinate systems, and for integrating over finite element meshes. -
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Stellarium
GPL software which renders realistic skies in real time
...It is available for Linux/Unix, Windows and macOS. With Stellarium, you really see what you can see with your eyes, binoculars or a small telescope. Stellarium is a free open source planetarium for your computer. It shows a realistic sky in 3D, just like what you see with the naked eye, binoculars or a telescope. Plugin system adding artifical satellites, ocular simulation, telescope control and more. Ability to add new solar system objects from online resources. Add your own deep sky objects, landscapes, constellation images, scripts, etc. ... -
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city-roads
Visualization of all roads within any city
...Because road topology reflects historical, geographic, and planning decisions, the resulting images serve as both analytical tools and generative art. Developers can integrate it into web pages or interactive dashboards where geographic structure is central, and users can pan/zoom to compare different cities or neighborhoods. -
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ReactiveMP.jl
High-performance reactive message-passing based Bayesian engine
...The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets. -
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Neuroglancer
WebGL-based viewer for volumetric data
...The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools. -
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Gephi
Gephi the open graph Viz platform
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks. ... -
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forecast
Forecasting Functions for Time Series and Linear Models
The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc.
