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  • Digital Payments by Deluxe Payment Exchange Icon
    Digital Payments by Deluxe Payment Exchange

    A single integrated payables solution that takes manual payment processes out of the equation, helping reduce risk and cutting costs for your business

    Save time, money and your sanity. Deluxe Payment Exchange+ (DPX+) is our integrated payments solution that streamlines and automates your accounts payable (AP) disbursements. DPX+ ensures secure payments and offers suppliers alternate ways to receive funds, including mailed checks, ACH, virtual credit cards, debit cards, or eCheck payments. By simply integrating with your existing accounting software like QuickBooks®, you’ll implement efficient payment solutions for AP with ease—without costly development fees or untimely delays.
  • Propelling Payments for Software Platforms Icon
    Propelling Payments for Software Platforms

    For SaaS businesses to monetize payments through its turnkey PayFac-as-a-Service solution.

    Exact Payments delivers easy-to-integrate embedded payment solutions enabling you to rapidly onboard merchants, instantly activate a variety of payment methods and accelerate your revenue — delivering an end-to-end payment processing platform for SaaS businesses.
  • 1
    KittyTerminalImages.jl

    KittyTerminalImages.jl

    Allows Julia to display images in the kitty terminal editor

    A package that allows Julia to display images in the kitty terminal editor.
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  • 2
    Gnuplot.jl

    Gnuplot.jl

    Julia interface to gnuplot

    Gnuplot.jl is a simple package able to send both data and commands from Julia to an underlying gnuplot process. Its main purpose it to provide a fast and powerful data visualization framework, using an extremely concise Julia syntax. It also has automatic display of plots in Jupyter, Juno and VS Code.
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  • 3
    DecisionTree.jl

    DecisionTree.jl

    Julia implementation of Decision Tree (CART) Random Forest algorithm

    Julia implementation of Decision Tree (CART) and Random Forest algorithms.
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  • 4
    PythonCall & JuliaCall

    PythonCall & JuliaCall

    Python and Julia in harmony

    Bringing Python® and Julia together in seamless harmony. Call Python code from Julia and Julia code from Python via a symmetric interface. Simple syntax, so the Python code looks like Python and the Julia code looks like Julia. Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control. Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array. array, numpy.ndarray) from Julia or Julia arrays from...
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  • The next chapter in business mental wellness Icon
    The next chapter in business mental wellness

    Entrust your employee well-being to Calmerry's nationwide network of licensed mental health professionals.

    Calmerry is beneficial for businesses of all sizes, particularly those in high-stress industries, organizations with remote teams, and HR departments seeking to improve employee well-being and productivity
  • 5
    DynamicQuantities.jl

    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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  • 6
    InteractiveErrors.jl

    InteractiveErrors.jl

    Interactive error messages for the Julia REPL

    Interactive error messages for the Julia REPL. Just start using your REPL normally. Once you hit an error you'll be presented with an interactive tree representing your stacktrace which you can explore. To turn interactive errors off and return to using normal stack traces call toggle(). Call toggle() again to turn it back on. Press up and down arrows to move through the stacktrace. Press space to fold or unfold the currently selected line. A + will appear on folded lines. Press enter once...
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  • 7
    Gaston.jl

    Gaston.jl

    A julia front-end for gnuplot

    Gaston is a Julia package for plotting. It provides an interface to gnuplot, a powerful plotting package available on all major platforms. The current stable release is v1.1.0, and it has been tested with Julia LTS (1.6) and stable (1.8), on Linux. Gaston should work on any platform that runs gnuplot.
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  • 8
    Rotations.jl

    Rotations.jl

    Julia implementations for different rotation parameterizations

    3D rotations made easy in Julia. This package implements various 3D rotation parameterizations and defines conversions between them. At their heart, each rotation parameterization is a 3×3 unitary (orthogonal) matrix (based on the StaticArrays.jl package), and acts to rotate a 3-vector about the origin through matrix-vector multiplication. While the RotMatrix type is a dense representation of a 3×3 matrix, we also have sparse (or computed, rather) representations such as quaternions,...
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  • 9
    BlockArrays.jl

    BlockArrays.jl

    BlockArrays for Julia

    A block array is a partition of an array into blocks or subarrays, see Wikipedia for a more extensive description. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different types of block arrays that follow the AbstractBlockArray interface. The type...
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  • JobNimbus Construction Software Icon
    JobNimbus Construction Software

    For Roofers, Remodelers, Contractors, Home Service Industry

    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.
  • 10
    CoordinateTransformations.jl

    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...
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  • 11
    Literate

    Literate

    Simple package for literate programming in Julia

    Literate is a package for Literate Programming. The main purpose is to facilitate writing Julia examples/tutorials that can be included in your package documentation. Literate can generate markdown pages (for e.g. Documenter.jl), and Jupyter notebooks, from the same source file. There is also an option to "clean" the source from all metadata, and produce a pure Julia script. Using a single source file for multiple purposes reduces maintenance, and makes sure your different output formats are...
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  • 12
    Agents.jl

    Agents.jl

    Agent-based modeling framework in Julia

    Agents.jl is a pure Julia framework for agent-based modeling (ABM): a computational simulation methodology where autonomous agents react to their environment (including other agents) given a predefined set of rules. The simplicity of Agents.jl is due to the intuitive space-agnostic modeling approach we have implemented: agent actions are specified using generically named functions (such as "move agent" or "find nearby agents") that do not depend on the actual space the agents exist in, nor...
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  • 13
    Oceananigans.jl

    Oceananigans.jl

    Julia software for fast, friendly, flexible fluid dynamics on CPUs

    Oceananigans is a fast, friendly, flexible software package for finite volume simulations of the nonhydrostatic and hydrostatic Boussinesq equations on CPUs and GPUs. It runs on GPUs (wow, fast!), though we believe Oceananigans makes the biggest waves with its ultra-flexible user interface that makes simple simulations easy, and complex, creative simulations possible.
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  • 14
    Pluto.jl

    Pluto.jl

    Simple reactive notebooks for Julia plutojl.org

    We are on a mission to make scientific computing more accessible and fun. Writing a notebook is not just about writing the final document, Pluto empowers the experiments and discoveries that are essential to getting there.
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  • 15
    BetaML.jl

    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...
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  • 16
    InteractiveViz.jl

    InteractiveViz.jl

    Interactive visualization tools for Julia

    Julia already has a rich set of plotting tools in the form of the Plots and Makie ecosystems, and various backends for these. So why another plotting package? InteractiveViz is not a replacement for Plots or Makie, but rather a graphics pipeline system developed on top of Makie. It has a few objectives. To provide a simple API to visualize large or possibly infinite datasets (tens of millions of data points) easily. To enable interactivity, and be responsive even with large amounts of data...
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  • 17
    LoggingExtras.jl

    LoggingExtras.jl

    Composable Loggers for the Julia Logging StdLib

    LoggingExtras allows routing logged information to different places when constructing complicated "log plumbing" systems. Built upon the concept of simple parts composed together, subtyping AbstractLogger provides a powerful and flexible definition for your logging system without a need to define any custom loggers. When we talk about composability, the composition of any set of Loggers is itself a Logger, and LoggingExtras is a composable logging system.
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  • 18
    GMT.jl

    GMT.jl

    Generic Mapping Tools Library Wrapper for Julia

    The Generic Mapping Tools, GMT, is an open source collection of tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x–y plots via contour maps to artificially illuminated surfaces and 3D perspective views. This link will take you to an impressive collection of figures made with GMT. The GMT Julia wrapper was designed to work in a way the close as possible...
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  • 19
    NeuralOperators.jl

    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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  • 20
    Roots.jl

    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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  • 21
    AutoMLPipeline.jl

    AutoMLPipeline.jl

    Package that makes it trivial to create and evaluate machine learning

    AutoMLPipeline (AMLP) is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica...
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  • 22
    HDF5.jl

    HDF5.jl

    Save and load data in the HDF5 file format from Julia

    HDF5 stands for Hierarchical Data Format v5 and is closely modeled on file systems. In HDF5, a "group" is analogous to a directory, a "dataset" is like a file. HDF5 also uses "attributes" to associate metadata with a particular group or dataset. HDF5 uses ASCII names for these different objects, and objects can be accessed by Unix-like pathnames, e.g., "/sample1/tempsensor/firsttrial" for a top-level group "sample1", a subgroup "tempsensor", and a dataset "firsttrial". For simple types (scalars...
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  • 23
    Catalyst.jl

    Catalyst.jl

    Chemical reaction network and systems biology interface

    Catalyst.jl is a symbolic modeling package for analysis and high-performance simulation of chemical reaction networks. Catalyst defines symbolic ReactionSystems, which can be created programmatically or easily specified using Catalyst's domain-specific language (DSL). Leveraging ModelingToolkit and Symbolics.jl, Catalyst enables large-scale simulations through auto-vectorization and parallelism. Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy...
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  • 24
    Makie

    Makie

    Interactive data visualizations and plotting in Julia

    Makie is an interactive data visualization and plotting ecosystem for the Julia programming language, available on Windows, Linux, and Mac. The backend packages GLMakie, WGLMakie, CairoMakie and RPRMakie add different functionalities: You can use Makie to interactively explore your data and create simple GUIs in native Windows or web browsers, export high-quality vector graphics or even raytrace with physically accurate lighting. Choose one or more backend packages: GLMakie (interactive OpenGL...
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  • 25
    FLoops.jl

    FLoops.jl

    Fast sequential, threaded, and distributed for-loops for Julia

    Fast sequential, threaded, and distributed for-loops for Julia, fold for humans.FLoops.jl provides a macro @floop. It can be used to generate a fast generic sequential and parallel iteration over complex collections. Furthermore, the loop written in @floop can be executed with any compatible executors. See FoldsThreads.jl for various thread-based executors that are optimized for different kinds of loops. FoldsCUDA.jl provides an executor for GPU. FLoops.jl also provides a simple distributed...
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