Search Results for "f-droid" - Page 2
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Showing 826 open source projects for "f-droid"
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We design our technology to make workforce management easier. APS offers core HR, payroll, benefits administration, attendance, recruiting, employee onboarding, and more.
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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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FVim
Cross platform Neovim front-end UI, built with F# + Avalonia
Cross platform Neovim front-end UI, built with F# + Avalonia. Download the latest release package for your system, extract and run FVim! For Windows 7 / Vista / 8.1 / Server 2008 R2 / Server 2012 R2, use the win7-x64 package. For Windows 10, use the win-x64 package -- this version has faster startup. For macOS, it's packaged as an app bundle, unzip and drag it to your applications folder. Use a Windows FVim frontend with a WSL neovim: fvim, wsl. Multi-grid support, try Ctrl-w ge to detach... -
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Bogus
A simple and sane fake data generator for C#, F#, and VB.NET
Bogus is a simple and sane fake data generator for .NET languages like C#, F# and VB.NET. Bogus is fundamentally a C# port of faker.js and inspired by FluentValidation's syntax sugar. Bogus will help you load databases, UI and apps with fake data for your testing needs. When Bogus updates locales from faker.js or issues bug fixes, sometimes deterministic sequences can change. Changes to deterministic outputs are usually highlighted in the release notes. Changes to deterministic outputs is also... -
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology... -
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Framework Benchmarks
Source for the TechEmpower Framework Benchmarks project
If you're new to the project, welcome! Please feel free to ask questions here. We encourage new frameworks and contributors to ask questions. We're here to help! This project provides representative performance measures across a wide field of web application frameworks. With much help from the community, coverage is quite broad and we are happy to broaden it further with contributions. The project presently includes frameworks on many languages including Go, Python, Java, Ruby, PHP, C#, F... -
Track leads, jobs, and tasks from one easy to use software. You can access your information wherever you are, get everyone on the same page, and grow your business.
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.NET Interactive
.NET Interactive takes .NET and embeds it into your experiences
.NET Interactive takes the power of .NET and embeds it into your interactive experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before. We recently introduced the .NET Interactive Notebooks extension for Visual Studio Code, which adds support for .NET Interactive using the new Visual Studio Code native notebook feature. We encourage you to try it out. .NET Interactive enables users to mix languages in a single notebook or cell without a wrapper. The... -
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SST
Build serverless apps. Set breakpoints and test your functions locally
SST is an open-source serverless application platform that deploys to your AWS account, helping you go from idea to IPO. Work on your local Lambda functions lives, without mocking or redeploying your app. Higher-level CDK constructs are made specifically for building serverless apps. Manage the resources in your application with the SST Console. Traditionally, we’ve built and deployed web applications where we have some degree of control over the HTTP requests that are made to our server.... -
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Fable
F# to JavaScript compiler
Type inference provides robustness and correctness, but without the cost of additional code. Let the compiler catch bugs for you. Fable produces readable JavaScript code compatible with ES2015 standards and popular tooling like Webpack. Call JavaScript from Fable or Fable from JS. Use NPM packages. The entire JavaScript ecosystem is at your fingertips. Choose your favorite tool, from Visual Studio Code to JetBrains Rider. Fable supports the F# core library and some common .NET libraries... -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations... -
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FSharp.Data
F# Data: Library for Data Access
The FSharp.Data package implements core functionality to access common data formats in your F# applications and scripts. It contains F# type providers for working with structured file formats (CSV, HTML, JSON and XML) and helpers for parsing CSV, HTML and JSON files and for sending HTTP requests. This library focuses on providing simple access to structured documents and other data sources. The FSharp.Data type providers for CSV, HTML, JSON and XML infer types from the structure of a sample... -
Venn is a secure workspace for remote work that isolates and protects work from any personal use on the same computer. Work lives in a secure local enclave that is company controlled, where all data is encrypted and access is managed. Within the enclave – visually indicated by the Blue Border around these applications – business activity is walled off from anything that happens on the personal side. As a result, work and personal uses can now safely coexist on the same computer.
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HCubature.jl
Pure-Julia multidimensional h-adaptive integration
The HCubature module is a pure-Julia implementation of multidimensional "h-adaptive" integration. then hcubature(f, a, b) computes the integral, adaptively subdividing the integration volume into smaller and smaller pieces until convergence is achieved to the desired tolerance (specified by optional rtol and atol keyword arguments. Because hcubature is written purely in Julia, the integrand f(x) can return any vector-like object (technically, any type supporting +, -, * real, and norm: a Banach... -
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Roots.jl
Root finding functions for Julia
This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known (one... -
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UnROOT.jl
Native Julia I/O package to work with CERN ROOT files objects
UnROOT.jl is a reader for the CERN ROOT file format written entirely in Julia, without any dependence on ROOT or Python. -
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FrankWolfe.jl
Julia implementation for various Frank-Wolfe and Conditional Gradient
This package is a toolbox for Frank-Wolfe and conditional gradient algorithms. Frank-Wolfe algorithms were designed to solve optimization problems where f is a differentiable convex function and C is a convex and compact set. They are especially useful when we know how to optimize a linear function over C in an efficient way. -
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React Joyride
Create guided tours in your apps
Showcase your app to new users or explain functionality of new features. It uses react-floater for positioning and styling. And you can use your own components too! -
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ThreadsX.jl
Parallelized Base functions
... a subset of API provided by Base. Everything inside ThreadsX.Implementations is an implementation detail. The public API functions of ThreadsX expect that the data structure and function(s) passed as argument are "thread-friendly" in the sense that operating on distinct elements in the given container from multiple tasks in parallel is safe. For example, ThreadsX.sum(f, array) assumes that executing f(::eltype(array)) and accessing elements as in array[i] from multiple threads is safe. -
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ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD). While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms (such as finite-differencing) in both speed and accuracy. Functions like f which map a vector to a scalar are the best case... -
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q Go
Quick and dirty debugging output for tired Go programmers
q is a better way to do print statement debugging. For best results, dedicate a terminal to tailing $TMPDIR/q while you work. You also can simply tail -f $TMPDIR/q, but it's highly recommended to use the provided commands. Type q.Q instead of fmt.Printf and your variables will be printed like the provided example. Faster to type, pretty-printed vars and expressions. Easier to see inside structs, doesn't go to noisy-ass stdout. It goes to $TMPDIR/q. q Go offers pretty colors! -
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function... -
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Mixed-effects models in Julia
A Julia package for fitting (statistical) mixed-effects models
... Treatment 1 versus the placebo". If the potential levels of the covariate are fixed and reproducible, e.g. the levels for Sex could be "F" and "M", they are modeled with fixed-effects parameters. If the levels constitute a sample from a population, e.g. the Subject or the Item at a particular observation, they are modeled as random effects. -
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Emacs Markdown Mode
Emacs Markdown Mode
... in Emacs, extensions, configuration examples, tips and tricks, and a survey of other packages that work with Markdown Mode. Finally, Emacs is also a self-documenting editor. This means that the source code itself contains additional documentation: each function has its own docstring available via C-h f (describe-function), individual keybindings can be investigated with C-h k (describe-key), and a complete list of keybindings is available using C-h m (describe-mode). -
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OxyPlot
A cross-platform plotting library for .NET
... many different types of axes and series. If you need some functionality that is not included in the library, you can also create a derived class and override the rendering implementation. Make sure you reference and initialize the OxyPlot platform renderers, otherwise you will see nothing. The latest pre-release packages are pushed by AppVeyor CI to myget.org. To install these packages, set the myget.org package source https://www.myget.org/F/oxyplot and remember the "-pre" flag. -
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IVY
The Unified Machine Learning Framework
... an awesome model on GitHub, written in JAX. We'll use PerceiverIO as an example. Implement the model in PyTorch yourself, spending time and energy ensuring every detail is correct. Otherwise, wait for a PyTorch version to appear on GitHub, among the many re-implementation attempts that appear (a, b, c, d, e, f). Instantly transpile the JAX model to PyTorch. This creates an identical PyTorch equivalent of the original model. -
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fq
jq for binary formats
Tool, language, and decoders for working with binary data. fq is inspired by the well-known jq tool and language and allows you to work with binary formats the same way you would using jq. In addition, it can also present data similar to a hex viewer, transform, slice, and concatenate binary data, supports nested formats, and has an interactive REPL with auto-completion. It was originally designed to query, inspect and debug codecs and metadata in media files and containers like mp4, FLAC,... -
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Vimium C
A keyboard shortcut browser extension for keyboard-based navigation
A keyboard shortcut tool for keyboard-based page navigation and browser tab operations with advanced omnibar and global shortcuts. Vimium C is an open-source browser extension that provides keyboard-based inner-page navigation, browser tab operations, and an enhanced search panel, so you may take full advantage of your browser without a mouse or touchpad. It supports all original commands of Vimium and some new useful commands (a full list can be seen in a help dialog in the Vimium C Options... -
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Kubetail
Bash script to tail Kubernetes logs from multiple pods
Bash script that enables you to aggregate (tail/follow) logs from multiple pods into one stream. This is the same as running "kubectl logs -f " but for multiple pods. Just download the kubetail file (or any of the releases) and you're good to go. Note that you may need to run compinit for zsh to pick-up the changes in the competition after having upgraded from the non-abbreviated installation. If you're using a ZSH plugin manager, you can install kubetail as a plugin. kubetail itself doesn't...