Search Results for "front-end"
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Showing 22 open source projects for "front-end"
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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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JuliaSyntax
A Julia frontend, written in Julia
...The AST and tree data structures are usable but their APIs will evolve as we try out various use cases. Parsing to the standard Expr AST is always possible and will be stable. The intention is to extend this library over time to cover more of the Julia compiler front end. -
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GPUArrays
Reusable array functionality for Julia's various GPU backends
...This package is the counterpart of Julia's AbstractArray interface, but for GPU array types: It provides functionality and tooling to speed-up development of new GPU array types. This package is not intended for end users! Instead, you should use one of the packages that builds on GPUArrays.jl, such as CUDA.jl, oneAPI.jl, AMDGPU.jl, or Metal.jl. -
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LossFunctions.jl
Julia package of loss functions for machine learning
...The sole purpose of this package is to provide an efficient and extensible implementation of various loss functions used throughout Machine Learning (ML). It is thus intended to serve as a special purpose back-end for other ML libraries that require losses to accomplish their tasks. To that end we provide a considerable amount of carefully implemented loss functions, as well as an API to query their properties (e.g. convexity). Furthermore, we expose methods to compute their values, derivatives, and second derivatives for single observations as well as arbitrarily sized arrays of observations. ... -
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DiffEqFlux.jl
Pre-built implicit layer architectures with O(1) backprop, GPUs
DiffEqFlux.jl is a Julia library that combines differential equations with neural networks, enabling the creation of neural differential equations (neural ODEs), universal differential equations, and physics-informed learning models. It serves as a bridge between the DifferentialEquations.jl and Flux.jl libraries, allowing for end-to-end differentiable simulations and model training in scientific machine learning. DiffEqFlux.jl is widely used for modeling dynamical systems with learnable components. -
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DiffOpt.jl
Differentiating convex optimization programs w.r.t. program parameters
...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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GPUCompiler.jl
Reusable compiler infrastructure for Julia GPU backends
Reusable compiler infrastructure for Julia GPU backends. This package offers reusable compiler infrastructure and tooling for implementing GPU compilers in Julia. It is not intended for end users! Instead, you should use one of the packages that builds on GPUCompiler.jl, such as CUDA.jl or AMDGPU.jl. -
8
Bumper.jl
Bring Your Own Stack
Bumper.jl is a package that aims to make working with bump allocators (also known as arena allocators) easier and safer. You can dynamically allocate memory to these bump allocators, and reset them at the end of a code block, just like Julia's stack. Allocating to a bump allocator with Bumper.jl can be just as efficient as stack allocation. Bumper.jl is still a young package, and may have bugs. Let me know if you find any. -
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PhysicalConstants.jl
Collection of fundamental physical constants with uncertainties
PhysicalConstants.jl provides common physical constants. They are defined as instances of the new Constant type, which is a subtype of AbstractQuantity (from Unitful.jl package) and can also be turned into Measurement objects (from Measurements.jl package) at request. Constants are grouped into different submodules so that the user can choose different datasets as needed. Currently, 2014 and 2018 editions of CODATA recommended values of the fundamental physical constants are provided. -
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10
Chain.jl
A Julia package for piping a value through transformation expressions
A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality. -
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MarketData.jl
Time series market data
The MarketData package provides open-source financial data for research and testing. The data is from Quandl and is free end-of-day stock data. It is public domain without restrictions. The TimeSeries TimeArray data structure is used to store the data, but conversion to other data structures, including DataFrames and AxisArrays, is supported. -
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Metal.jl
Metal programming in Julia
With Metal.jl it's possible to program GPUs on macOS using the Metal programming framework. The package is a work in progress. There are bugs, functionality is missing, and performance hasn't been optimized. Expect to have to make changes to this package if you want to use it. PRs are very welcome. These requirements are fairly strict, and are due to our limited development resources (manpower, hardware). Technically, they can be relaxed. If you are interested in contributing to this, see... -
13
JuliaWorkshop
Intensive Julia workshop that takes you from zero to hero
...Nevertheless, it assumes only rudimentary programming familiarity and does explain concepts that go beyond the basics. The goal of the workshop is to take you from zero to hero (regarding Julia): even if you know nothing about Julia, by the end you should be able to use it like a pro. The material has been updated during July-December 2023 to Julia v1.9+ and the corresponding latest stable versions of used packages -
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BinaryBuilder
Binary Dependency Builder for Julia
...Building binary packages is a pain. BinaryBuilder follows a philosophy that is similar to that of building Julia itself; when you want something done right, you do it yourself. To that end, BinaryBuilder is designed from the ground up to facilitate the building of packages within an easily reproducible and reliable Linux environment, ensuring that the built libraries and executables are deployable to every platform that Julia itself will run on. Packages are cross-compiled using a sequence of shell commands, packaged up inside tarballs, and hosted online for all to enjoy. ... -
15
AbstractGPs.jl
Abstract types and methods for Gaussian Processes
AbstractGPs.jl is a package that defines a low-level API for working with Gaussian processes (GPs), and basic functionality for working with them in the simplest cases. As such it is aimed more at developers and researchers who are interested in using it as a building block than end-users of GPs. You may want to go through the main API design documentation. -
16
LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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AI-Agent-Host
The AI Agent Host is a module-based development environment.
The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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19
ACME.jl
Analog Circuit Modeling and Emulation for Julia
ACME is a Julia package for the simulation of electrical circuits, focusing on audio effect circuits. It allows one to programmatically describe a circuit in terms of elements and connections between them and then automatically derive a model for the circuit. The model can then be run on varying input data. -
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MLDataUtils.jl
Utility package for generating, loading, and processing ML datasets
This package is designed to be the end-user facing front-end to all the data related functionality that is spread out across the JuliaML ecosystem. Most of the following sub-categories are covered by a single back-end package that is specialized on that specific problem. Consequently, if one of the following topics is of special interest to you, make sure to check out the corresponding documentation of that package. -
21
ReplMaker.jl
Simple API for building repl modes in Julia
...Suppose you've invented some language called MyLang and you've implemented a parser that turns MyLang code into Julia code which is then supposed to be executed by the Julia runtime. With ReplMaker.jl, you can simply hook your parser into the package and ReplMaker will then create a REPL mode where end users just type MyLang code and have it executed automatically. My hope is for this to be useful to someone who implements a full language or DSL in Julia that uses syntax not supported by Julia's parser and doesn't want to deal with the headache of making their own REPL mode. -
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Personal Library
Acts like a real library with the best user interface on the backpack.
Stores your favorites Books. Lets you track the Users logged,signed up. Time tracing of system access. Delete, and Add both Categories and Books. No fussy configurations, embedded database with Java Runtime Environment enabled.
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